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  • 101.
    Johns, Rasmus Johns
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Intelligent Formation Control using Deep Reinforcement Learning2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis, deep reinforcement learning is applied to the problem of formation control to enhance performance. The current state-of-the-art formation control algorithms are often not adaptive and require a high degree of expertise to tune. By introducing reinforcement learning in combination with a behavior-based formation control algorithm, simply tuning a reward function can change the entire dynamics of a group. In the experiments, a group of three agents moved to a goal which had its direct path blocked by obstacles. The degree of randomness in the environment varied: in some experiments, the obstacle positions and agent start positions were fixed between episodes, whereas in others they were completely random. The greatest improvements were seen in environments which did not change between episodes; in these experiments, agents could more than double their performance with regards to the reward. These results could be applicable to both simulated agents and physical agents operating in static areas, such as farms or warehouses. By adjusting the reward function, agents could improve the speed with which they approach a goal, obstacle avoidance, or a combination of the two. Two different and popular reinforcement algorithms were used in this work: Deep Double Q-Networks (DDQN) and Proximal Policy Optimization (PPO). Both algorithms showed similar success.

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  • 102.
    Jonsson, Niclas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Implementation and testing of an FPT-algorithm for computing the h+ heuristic2017Independent thesis Basic level (degree of Bachelor), 10,5 credits / 16 HE creditsStudent thesis
    Abstract [en]

    We have implemented and benchmarked an FPT-algorithm, that has two input parameters, k and w besides the input problem instance, which is a planing instance, in this thesis. The algorithm has an exponential running time as a function of these two parameters. The implemented algorithm computes the heuristic value h^+(s) of a state s that belongs to a state space, which originates from a strips instance. The purpose of the project was to test if the algorithm can be used to compute the heuristic function h^+, i.e. the delete-relaxation heuristic, in practice. The delete-relaxation heuristic value for some state is the length of the optimal solution from the state to a goal in the delete-relaxed-instance, which is the original instance without all its negative effects. Planning instances was benchmarked with the search algorithm A^* to test the algorithms practical value. The heuristic function blind was benchmarked together with A^* with the same instances so that we could compare the quality of the benchmark result for the implemented algorithm. The conclusion of the project was that the implemented algorithm is too slow to be used in practise.

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  • 103.
    Karlsson, Rickard
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Törnqvist, David
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application2008In: Proceedings of Reglermöte 2008, 2008, p. 313-322Conference paper (Other academic)
    Abstract [en]

    This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. Thesecond one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle modelsare computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithmfuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

  • 104.
    Karlsson, Rickard
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Törnqvist, David
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application2008In: Proceedings of the 2008 IEEE Aerospace Conference, 2008, p. 1-10Conference paper (Refereed)
    Abstract [en]

    This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. The second one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle models are computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithm fuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

  • 105.
    Karlsson, Rickard
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Schön, Thomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Törnqvist, David
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Conte, Gianpolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application2008Report (Other academic)
    Abstract [en]

    This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. Thesecond one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle modelsare computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithmfuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

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  • 106.
    Keisala, Simon
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Designing an Artificial Neural Network for state evaluation in Arimaa: Using a Convolutional Neural Network2017Independent thesis Basic level (university diploma), 10,5 credits / 16 HE creditsStudent thesis
    Abstract [en]

    Agents being able to play board games such as Tic Tac Toe, Chess, Go and Arimaa has been, and still is, a major difficulty in Artificial Intelligence. For the mentioned board games, there is a certain amount of legal moves a player can do in a specific board state. Tic Tac Toe have in average around 4-5 legal moves, with a total amount of 255168 possible games. Both Chess, Go and Arimaa have an increased amount of possible legal moves to do, and an almost infinite amount of possible games, making it impossible to have complete knowledge of the outcome.

    This thesis work have created various Neural Networks, with the purpose of evaluating the likelihood of winning a game given a certain board state. An improved evaluation function would compensate for the inability of doing a deeper tree search in Arimaa, and the anticipation is to compete on equal skills against another well-performing agent (meijin) having one less search depth.

    The results shows great potential. From a mere one hundred games against meijin, the network manages to separate good from bad positions, and after another one hundred games able to beat meijin with equal search depth.

    It seems promising that by improving the training and by testing different sizes for the neural network that a neural network could win even with one less search depth. The huge branching factor of Arimaa makes such an improvement of the evaluation beneficial, even if the evaluation would be 10 000 times more slow.

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  • 107.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. IRobot, Linkoping, Sweden; FaceMap LLC, CA 90265 USA.
    The Low-Cost Evolution of AI in Domestic Floor Cleaning Robots2018In: The AI Magazine, ISSN 0738-4602, Vol. 39, no 2, p. 89-90Article in journal (Other academic)
    Abstract [en]

    This article discusses AI methods deployed on domestic floor cleaning robots in the recent past and the way in which those methods are changing today. Formerly, innovations were tightly coupled with a price point customers were willing to pay. Today, there is a substantial increase in the AI found in these systems, driven by new challenges and scalable infrastructures.

  • 108.
    Kleiner, Alexander
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Farinelli, A.
    University of Verona, Italy.
    Ramchurn, S.
    University of Southampton, UK.
    Shi, B.
    Wuhan University of Tec., China.
    Maffioletti, F.
    University of Verona, Italy.
    Reffato, R.
    University of Verona, Italy.
    RMASBench: Benchmarking Dynamic Multi-Agent Coordination in Urban Search and Rescue2013In: Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013, p. 1195-1196Conference paper (Refereed)
    Abstract [en]

    We propose RMASBench, a new benchmarking tool based on the RoboCup Rescue Agent simulation system, to easily compare coordination approaches in a dynamic rescue scenario. In particular, we offer simple interfaces to plug-in coordination algorithms without the need for implementing and tuning low-level agents behaviors. Moreover, we add to the realism of the simulation by providing a large scale crowd simulator, which exploits GPUs parallel architecture, to simulate the behavior of thousands of agents in real time. Finally, we focus on a specific coordination problem where fire fighters must combat fires and prevent them from spreading across the city. We formalize this problem as a Distributed Constraint Optimization Problem and we compare two state-of-the art solution techniques: DSA and MaxSum. We perform an extensive empirical evaluation of such techniques considering several standard measures for performance (e.g. damages to buildings) and coordination overhead (e.g., message exchanged and non concurrent constraint checks). Our results provide interesting insights on limitations and benefits of DSA and MaxSum in our rescue scenario and demonstrate that RMASBench offers powerful tools to compare coordination algorithms in a dynamic environment.

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    AAMAS-2013-RMASBench.pdf
  • 109.
    Kleiner, Alexander
    et al.
    iRobot Corp, MA 01730 USA.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Tadokoro, Satoshi
    Tohoku University, Japan.
    Editorial: Special Issue on Safety, Security, and Rescue Robotics (SSRR), Part 12016In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967, Vol. 33, no 3, p. 263-264Article in journal (Other academic)
    Abstract [en]

    n/a

  • 110.
    Kleiner, Alexander
    et al.
    iRobot Corp, MA 01730 USA.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Tadokoro, Satoshi
    Tohoku University, Japan.
    Editorial: Special Issue on Safety, Security, and Rescue Robotics (SSRR), Part 22016In: Journal of Field Robotics, ISSN 1556-4959, E-ISSN 1556-4967, Vol. 33, no 4, p. 409-410Article in journal (Other academic)
    Abstract [en]

    n/a

  • 111.
    Kleiner, Alexander
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kolling, Andreas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Guaranteed Search With Large Teams of Unmanned Aerial Vehicles2013In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), IEEE conference proceedings, 2013, p. 2977-2983Conference paper (Refereed)
    Abstract [en]

    We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.

  • 112.
    Kolling, Andreas
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Multi-UAV Trajectory Planning for Guaranteed Search2013In: Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013, p. 79-86Conference paper (Refereed)
    Abstract [en]

    We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.

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    AAMAS-2013-Multi-UAV-Motion-Planning-for-Guaranteed-Search.pdf
  • 113.
    Kolling, Andreas
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Fast Guaranteed Search With Unmanned Aerial Vehicles2013In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), IEEE , 2013, p. 6013-6018Conference paper (Refereed)
    Abstract [en]

    In this paper we consider the problem of searching for an arbitrarily smart and fast evader in a large environment with a team of unmanned aerial vehicles (UAVs) while providing guarantees of detection. Our emphasis is on the fast execution of efficient search strategies that minimize the number of UAVs and the search time. We present the first approach for computing fast search strategies utilizing additional searchers to speed up the execution time and thereby enabling large scale UAV search. In order to scale to very large environments when using UAVs one would either have to overcome the energy limitations of UAVs or pay the cost of utilizing additional UAVs to speed up the search. Our approach is based on coordinating UAVs on sweep lines, covered by the UAV sensors, that move simultaneously through an environment. We present some simulation results that show a significant reduction in execution time when using multiple UAVs and a demonstration of a real system with three ARDrones. 

  • 114.
    Krysander, Mattias
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Roll, Jacob
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Dynamic Test Selection for Reconfigurable Diagnosis2008In: Proceedings of the 47th IEEE Conference on Decision and Control, IEEE , 2008, p. 1066-1072Conference paper (Refereed)
    Abstract [en]

    Detecting and isolating multiple faults is a computationally intense task which typically consists of computing a set of tests, and then computing the diagnoses based on the test results. This paper proposes a method to reduce the computational burden by only running the tests that are currently needed, and dynamically starting new tests when the need changes. A main contribution is a method to select tests such that the computational burden is reduced while maintaining the isolation performance of the diagnostic system. Key components in the approach are the test selection algorithm, the test initialization procedures, and a knowledge processing framework that supports the functionality needed. The approach is exemplified on a relatively small dynamical system, which still illustrates the complexity and possible computational gain with the proposed approach.

  • 115.
    Källström, Johan
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Adaptive Agent-Based Simulation for Individualized Training2020In: Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems(AAMAS 2020) / [ed] B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, G. Sukthankar, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org) , 2020, p. 2193-2195Conference paper (Refereed)
    Abstract [en]

    Agent-based simulation can be used for efficient and effective training of human operators and decision-makers. However, constructing realistic behavior models for the agents is challenging and time-consuming, especially for subject matter experts, who may not have expertise in artificial intelligence. In this work, we investigate how machine learning can be used to adapt simulation contents to the current needs of individual trainees. Our initial results demonstrate that multi-objective multi-agent reinforcement learning is a promising approach for creating agents with diverse and adaptive characteristics, which can stimulate humans in training.

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  • 116.
    Källström, Johan
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Multi-Agent Multi-Objective Deep Reinforcement Learning for Efficient and Effective Pilot Training2019In: Proceedings of the 10th Aerospace Technology Congress / [ed] Ingo Staack and Petter Krus, 2019, p. 101-111Conference paper (Refereed)
    Abstract [en]

    The tactical systems and operational environment of modern fighter aircraft are becoming increasingly complex. Creating a realistic and relevant environment for pilot training using only live aircraft is difficult, impractical and highly expensive. The Live, Virtual and Constructive (LVC) simulation paradigm aims to address this challenge. LVC simulation means linking real aircraft, ground-based systems and soldiers (Live), manned simulators (Virtual) and computer controlled synthetic entities (Constructive). Constructive simulation enables realization of complex scenarios with a large number of autonomous friendly, hostile and neutral entities, which interact with each other as well as manned simulators and real systems. This reduces the need for personnel to act as role-players through operation of e.g. live or virtual aircraft, thus lowering the cost of training. Constructive simulation also makes it possible to improve the availability of training by embedding simulation capabilities in live aircraft, making it possible to train anywhere, anytime. In this paper we discuss how machine learning techniques can be used to automate the process of constructing advanced, adaptive behavior models for constructive simulations, to improve the autonomy of future training systems. We conduct a number of initial experiments, and show that reinforcement learning, in particular multi-agent and multi-objective deep reinforcement learning, allows synthetic pilots to learn to cooperate and prioritize among conflicting objectives in air combat scenarios. Though the results are promising, we conclude that further algorithm development is necessary to fully master the complex domain of air combat simulation.

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  • 117.
    Källström, Johan
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Reinforcement Learning for Computer Generated Forces using Open-Source Software2019In: Proceedings of the 2019 Interservice/Industry Training, Simulation, and Education Conference, 2019, p. 1-11, article id 19197Conference paper (Refereed)
    Abstract [en]

    The creation of behavior models for computer generated forces (CGF) is a challenging and time-consuming task, which often requires expertise in programming of complex artificial intelligence algorithms. This makes it difficult for a subject matter expert with knowledge about the application domain and the training goals to build relevant scenarios and keep the training system in pace with training needs. In recent years, machine learning has shown promise as a method for building advanced decision-making models for synthetic agents. Such agents have been able to beat human champions in complex games such as poker, Go and StarCraft. There is reason to believe that similar achievements are possible in the domain of military simulation. However, in order to efficiently apply these techniques, it is important to have access to the right tools, as well as knowledge about the capabilities and limitations of algorithms.   

    This paper discusses efficient applications of deep reinforcement learning, a machine learning technique that allows synthetic agents to learn how to achieve their goals by interacting with their environment. We begin by giving an overview of available open-source frameworks for deep reinforcement learning, as well as libraries with reference implementations of state-of-the art algorithms. We then present an example of how these resources were used to build a reinforcement learning environment for a CGF software intended to support training of fighter pilots. Finally, based on our exploratory experiments in the presented environment, we discuss opportunities and challenges related to the application of reinforcement learning techniques in the domain of air combat training systems, with the aim to efficiently construct high quality behavior models for computer generated forces.

  • 118.
    Källström, Johan
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Tunable Dynamics in Agent-Based Simulation using Multi-Objective Reinforcement Learning2019Conference paper (Refereed)
    Abstract [en]

    Agent-based simulation is a powerful tool for studying complex systems of interacting agents. To achieve good results, the behavior models used for the agents must be of high quality. Traditionally these models have been handcrafted by domain experts. This is a difficult, expensive and time consuming process. In contrast, reinforcement learning allows agents to learn how to achieve their goals by interacting with the environment. However, after training the behavior of such agents is often static, i.e. it can no longer be affected by a human. This makes it difficult to adapt agent behavior to specific user needs, which may vary among different runs of the simulation. In this paper we address this problem by studying how multi-objective reinforcement learning can be used as a framework for building tunable agents, whose characteristics can be adjusted at runtime to promote adaptiveness and diversity in agent-based simulation. We propose an agent architecture that allows us to adapt popular deep reinforcement learning algorithms to multi-objective environments. We empirically show that our method allows us to train tunable agents that can approximate the policies of multiple species of agents.

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    Tunable Dynamics in Agent-Based Simulation using Multi-Objective Reinforcement Learning
  • 119.
    Landén, David
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Complex Task Allocation in Mixed-Initiative Delegation: A UAV Case Study2012In: Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers / [ed] Nirmit Desai, Alan Liu, Michael Winikoff, Springer Berlin/Heidelberg, 2012, Vol. 7057, p. 288-303Conference paper (Refereed)
    Abstract [en]

    Unmanned aircraft systems (UASs) are now becoming technologically mature enough to be integrated into civil society. An essential issue is principled mixed-initiative interaction between UASs and human operators. Two central problems are to specify the structure and requirements of complex tasks and to assign platforms to these tasks. We have previously proposed Task Specification Trees (TSTs) as a highly expressive specification language for complex multi-agent tasks that supports mixed-initiative delegation and adjustable autonomy. The main contribution of this paper is a sound and complete distributed heuristic search algorithm for allocating the individual tasks in a TST to platforms. The allocation also instantiates the parameters of the tasks such that all the constraints of the TST are satisfied. Constraints are used to model dependencies between tasks, resource usage as well as temporal and spatial requirements on complex tasks. Finally, we discuss a concrete case study with a team of unmanned aerial vehicles assisting in a challenging emergency situation.

  • 120.
    Linder, Tova
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Jigin, Ola
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Organ Detection and Localization in Radiological Image Volumes2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Using Convolutional Neural Networks for classification of images and for localization and detection of objects in images is becoming increasingly popular. Within radiology a huge amount of image data is produced and meta data containing information of what the images depict is currently added manually by a radiologist. To aid in streamlining physician’s workflow this study has investigated the possibility to use Convolutional Neural Networks (CNNs) that are pre-trained on natural images to automatically detect the presence and location of multiple organs and body-parts in medical CT images. The results show promise for multiclass classification with an average precision 89.41% and average recall 86.40%. This also confirms that a CNN that is pre-trained on natural images can be succesfully transferred to solve a different task. It was also found that adding additional data to the dataset does not necessarily result in increased precision and recall or decreased error rate. It is rather the type of data and used preprocessing techniques that matter.

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  • 121.
    Löfgren, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    How may robots affect the labour market in the near future?2016In: Machines, jobs and equality: Technological changes and labour markets in Europe / [ed] Andreas Bergström and Karl Wennberg, The European Liberal Forum (ELF) , 2016, p. 105-134Chapter in book (Other academic)
    Abstract [en]

    This chapter discusses how different applications for robots will affect the labour market in the near future. Near future refers to the next 10-50 years. It is likely that several occupations will disappear, but new ones will also emerge. However, we claim that the net result will be negative, which means that we will have higher unemployment. These effects will not happen overnight, and not all occupations will be affected. But, this will happen for a sufficient amount of the population for it to become a problem for society.

    The observations made in this chapter are not from the point of view of a social scientist, but that of a roboticist. The observations are taken together with readings of scientific literature on automation. I do not claim to have answers to the economic and social scientific problems thrown up, but to raise a set of critical questions for the reader.

    All the examples in this chapter are real technologies that exist, not just in science-fiction or future technology. However, most of the examples are still in their research stage and are either not available for the general public, or still very expensive.

    No one can predict the future in detail, but this chapter tries to provide a scenario of the future of different kinds of occupations through the perspective of the field of robotics. I have been developing robots for 15 years and will use some examples that I have constructed, but also examples from other roboticists. The chapter does not discuss the risks of automation for all occupations, but instead focuses on blue-collar workers, such as machine operators, the transportation sector with the advent of driverless cars, white-collar workers in offices, skilled professions in the legal and medical spheres, and creative workers.

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    How may robots affect the labour market in the near future?
  • 122.
    Löfgren, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Dybeck, Jon
    Linköping University, University Services.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Qualification document: RoboCup 2015 Standard Platform League2015Conference paper (Other academic)
    Abstract [en]

    This is the application for the RoboCup 2015 StandardPlatform League from the ”LiU Robotics” team. In thisdocument we present ourselves and what we want to achieve byour participation in the conference and competition

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    Qualification document: RoboCup 2015 Standard Platform League
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    Linkoping Humanoids – Team Description
  • 123. Marconi, L.
    et al.
    Melchiorri, C.
    Beetz, M.
    Pangercic, D.
    Siegwart, R.
    Leutenegger, S.
    Carloni, R.
    Stramigioli, S.
    Bruyninckx, H.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Lippiello, V.
    Finzi, A.
    Siciliano, B.
    Sala, A.
    Tomatis, N.
    The SHERPA project: Smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments2012In: Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR), IEEE , 2012, p. 1-4Conference paper (Refereed)
    Abstract [en]

    The goal of the paper is to present the foreseen research activity of the European project “SHERPA” whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the “busy genius”, working in team with the ground vehicle, as the “intelligent donkey”, and with the aerial platforms, i.e. the “trained wasps” and “patrolling hawks”. Indeed, the research activity focuses on how the “busy genius” and the “SHERPA animals” interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.

  • 124.
    Moral López, Elena
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Muting pattern strategy for positioning in cellular networks.2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Location Based Services (LBS) calculate the position of the user for different purposes like advertising and navigation. Most importantly, these services are also used to help emergency services by calculating the position of the person that places the emergency phone call. This has introduced a number of requirements on the accuracy of the measurements of the position. Observed Time Difference of Arrival (OTDOA) is the method used to estimate the position of the user due to its high accuracy. Nevertheless, this method relies on the correct reception of so called positioning signals, and therefore the calculations can suffer from errors due to interference between the signals. To lower the probability of interference, muting patterns can be used. These methods can selectively mute certain signals to increase the signal to interference and noise ratio (SINR) of others and therefore the number of signals detected. In this thesis, a simulation environment for the comparison of the different muting patterns has been developed. The already existing muting patterns have been simulated and compared in terms of number of detected nodes and SINR values achieved. A new muting pattern has been proposed and compared to the others. The results obtained have been presented and an initial conclusion on which of the muting patterns offers the best performance has been drawn.

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  • 125.
    Nguyen, L.A.
    et al.
    Institute of Informatics, University of of Warsaw, Warsaw, Poland, VNU University of of Engineering and Technology, Hanoi, Viet Nam.
    Nguyen, T.-B.-L.
    Department of Information Technology, Hue University of of Sciences, Hue City, Viet Nam.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology. Institute of Informatics, University of Warsaw, Warsaw, Poland .
    On horn knowledge bases in regular description logic with inverse2014In: KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2013), VOL 1, Springer Berlin/Heidelberg, 2014, Vol. 244 VOLUME 1, p. 37-49Conference paper (Refereed)
    Abstract [en]

    We study a Horn fragment called Horn-RegI of the regular description logic with inverse RegI, which extends the description logic ALC with inverse roles and regular role inclusion axioms characterized by finite automata. In contrast to the well-known Horn fragmentsEL, DL-Lite, DLP, Horn-SH IQ and Horn-SROIQof description logics, Horn-RegI allows a form of the concept constructor universal restriction to appear at the left hand side of terminological inclusion axioms, while still has PTIME data complexity. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We provide an algorithm with PTIME data complexity for checking satisfiability of Horn-RegI knowledge bases.

  • 126.
    Nguyen, Linh Anh
    et al.
    Institute of Informatics, University of Warsaw, Warsaw, Poland; Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnamn.
    Nguyen, Thi-Bich-Loc
    Department of Information Technology, Hue University of Sciences, Hue, Vietnam.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    A Horn Fragment with PTime Data Complexity of Regular Description Logic with Inverse2014In: VNU Journal of Computer Science and Communication Engineering, ISSN 0866-8612, Vol. 30, no 4, p. 14-28Article in journal (Refereed)
    Abstract [en]

    We study a Horn fragment called Horn-RegI of the regular description logic with inverse RegI, which extends the description logic ALC with inverse roles and regular role inclusion axioms characterized by finite automata. In contrast to the well-known Horn fragments EL, DL-Lite, DLP, Horn-SHIQ and Horn-SROIQ of description logics, Horn-RegI allows a form of the concept constructor "universal restriction" to appear at the left hand side of terminological inclusion axioms, while still has PTIME data complexity. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We provide an algorithm with PTIME data complexity for checking satisfiability of Horn-RegI knowledge bases.

  • 127. Nguyen, Linh Anh
    et al.
    Nguyen, Thi-Bich-Loc
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    HornDL: An Expressive Horn Description Logic with PTime Data Complexity2013In: Web Reasoning and Rule Systems / [ed] Wolfgang Faber, Domenico Lembo, Springer Berlin/Heidelberg, 2013, p. 259-264Conference paper (Refereed)
    Abstract [en]

    We introduce a Horn description logic called Horn-DL, which is strictly and essentially richer than Horn- SROIQ , while still has PTime data complexity. In comparison with Horn- SROIQ , HornDL additionally allows the universal role and assertions of the form irreflexive (s), ¬s(a,b) , a≐̸b . More importantly, in contrast to all the well-known Horn fragments EL , DL-Lite, DLP, Horn- SHIQ , Horn- SROIQ of description logics, HornDL allows a form of the concept constructor “universal restriction” to appear at the left hand side of terminological inclusion axioms. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. In the long version of this paper, we present the first algorithm with PTime data complexity for checking satisfiability of HornDL knowledge bases.

  • 128.
    Nguyen, Linh Anh
    et al.
    Ton Duc Thang University, Vietnam; University of Warsaw, Poland.
    Nguyen, Thi-Bich-Loc
    Hue University of Sciences, Vietnam.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering. University of Warsaw, Poland.
    Towards richer rule languages with polynomial data complexity for the Semantic Web2015In: Data & Knowledge Engineering, ISSN 0169-023X, E-ISSN 1872-6933, Vol. 96-97, p. 57-77Article in journal (Refereed)
    Abstract [en]

    We introduce a Horn description logic called Horn-DL, which is strictly and essentially richer than Horn-Reg(1), Horn-SHTQ and Horn-SROIQ, while still has PTime data complexity. In comparison with Horn-SROIQ, Horn-DL additionally allows the universal role and assertions of the form irreflexive(s), -s(a, b), a b. More importantly, in contrast to all the well-known Horn fragments epsilon L, DL-Lite, DLP, Horn-SHIQ, and Horn-SROIQ of description logics, Horn-DL allows a form of the concept constructor "universal restriction" to appear at the left hand side of terminological inclusion axioms. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We develop the first algorithm with PTime data complexity for checking satisfiability of Horn-DL knowledge bases.

  • 129.
    Nguyen, Linh Anh
    et al.
    University of Warsaw, Poland.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Logic-Based Roughification2013In: Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam (vol. I) / [ed] Andrzej Skowron, Zbigniew Suraj, Springer Berlin/Heidelberg, 2013, 1, p. 517-543Chapter in book (Other academic)
    Abstract [en]

    This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being.This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches  discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches.We are proud to offer the readers this book. 

  • 130.
    Nguyen, Linh Anh
    et al.
    University of Warsaw, Poland.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Paraconsistent Reasoning for Semantic Web Agents2012In: Transactions on Computational Collective Intelligence VI / [ed] Ngoc Thanh Nguyen, Springer Berlin/Heidelberg, 2012, no 6, p. 36-55Chapter in book (Refereed)
    Abstract [en]

    The LNCS journal Transactions on Computational Collective Intelligence (TCCI) focuses on all facets of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems.

    This, the sixth issue of Transactions on Computational Collective Intelligence contains 10 selected papers, focusing on the topics of classification, agent cooperation, paraconsistent reasoning and agent distributed mobile interaction.

  • 131. Order onlineBuy this publication >>
    Nilsson, Mikael
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Efficient Temporal Reasoning with Uncertainty2015Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Automated Planning is an active area within Artificial Intelligence. With the help of computers we can quickly find good plans in complicated problem domains, such as planning for search and rescue after a natural disaster. When planning in realistic domains the exact duration of an action generally cannot be predicted in advance. Temporal planning therefore tends to use upper bounds on durations, with the explicit or implicit assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false. If we finish cooking too early, the dinner will be cold before everyone is at home and can eat. Simple Temporal Networks with Uncertainty (STNUs) allow us to model such situations. An STNU-based planner must verify that the temporal problems it generates are executable, which is captured by the property of dynamic controllability (DC). If a plan is not dynamically controllable, adding actions cannot restore controllability. Therefore a planner should verify after each action addition whether the plan remains DC, and if not, backtrack. Verifying dynamic controllability of a full STNU is computationally intensive. Therefore, incremental DC verification algorithms are needed.

    We start by discussing two existing algorithms relevant to the thesis. These are the very first DC verification algorithm called MMV (by Morris, Muscettola and Vidal) and the incremental DC verification algorithm called FastIDC, which is based on MMV.

    We then show that FastIDC is not sound, sometimes labeling networks as dynamically controllable when they are not.  We analyze the algorithm to pinpoint the cause and show how the algorithm can be modified to correctly and efficiently detect uncontrollable networks.

    In the next part we use insights from this work to re-analyze the MMV algorithm. This algorithm is pseudo-polynomial and was later subsumed by first an n5 algorithm and then an n4 algorithm. We show that the basic techniques used by MMV can in fact be used to create an n4 algorithm for verifying dynamic controllability, with a new termination criterion based on a deeper analysis of MMV. This means that there is now a comparatively easy way of implementing a highly efficient dynamic controllability verification algorithm. From a theoretical viewpoint, understanding MMV is important since it acts as a building block for all subsequent algorithms that verify dynamic controllability. In our analysis we also discuss a change in MMV which reduces the amount of regression needed in the network substantially.

    In the final part of the thesis we show that the FastIDC method can result in traversing part of a temporal network multiple times, with constraints slowly tightening towards their final values.  As a result of our analysis we then present a new algorithm with an improved traversal strategy that avoids this behavior.  The new algorithm, EfficientIDC, has a time complexity which is lower than that of FastIDC. We prove that it is sound and complete.

     

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  • 132.
    Nilsson, Mikael
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    On the Complexity of Finding Spanner Paths2013In: Booklet of Abstracts, The European Workshop on Computational Geometry (EuroCG) / [ed] Sandor P. Fekete, 2013, p. 77-80Conference paper (Refereed)
    Abstract [en]

    We study the complexity of finding so called spanner paths between arbitrary nodes in Euclidean graphs. We study both general Euclidean graphs and a special type of graphs called Integer Graphs. The problem is proven NP-complete for general Euclidean graphs with non-constant stretches (e.g. (2n)^(3/2) where n denotes the number of nodes in the graph). An algorithm solving the problem in O(2^(0.822n)) is presented. Integer graphs are simpler and for these special cases a better algorithm is presented. By using a partial order of so called Images the algorithm solves the spanner path problem using O(2^(c(\log n)^2)) time, where c is a constant depending only on the stretch.

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    On the Complexity of Finding Spanner Paths
  • 133.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Classical Dynamic Controllability Revisited: A Tighter Bound on the Classical Algorithm2014In: Proceedings of the 6th International Conference on Agents and Artificial Intelligence (ICAART), 2014, p. 130-141Conference paper (Refereed)
    Abstract [en]

    Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems wheresome durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essentialto verify that such networks are dynamically controllable (DC) – executable regardless of the outcomesof uncontrollable durations – and to convert them to an executable form. We use insights from incrementalDC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to bepseudo-polynomial and subsumed by an O(n5) algorithm and later an O(n4) algorithm, is in fact O(n4) givena small modification. This makes the algorithm attractive once again, given its basis in a less complex andmore intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

  • 134.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Efficient IDC: A Faster Incremental Dynamic Controllability Algorithm2014In: Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS), AAAI Press, 2014, p. 199-207Conference paper (Refereed)
    Abstract [en]

    Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential to verify that such networks are dynamically controllable (DC) – executable regardless of the outcomes of uncontrollable durations – and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to be pseudo-polynomial and subsumed by an O(n5) algorithm and later an O(n4) algorithm, is in fact O(n4) given a small modification. This makes the algorithm attractive once again, given its basis in a less complex and more intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

  • 135.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Efficient Processing of Simple Temporal Networks with Uncertainty: Algorithms for Dynamic Controllability Verification2016In: Acta Informatica, ISSN 0001-5903, E-ISSN 1432-0525, Vol. 53, no 6-8, p. 723-752Article in journal (Refereed)
    Abstract [en]

    Temporal formalisms are essential for reasoning about actions that are carried out over time. The exact durations of such actions are generally hard to predict. In temporal planning, the resulting uncertainty is often worked around by only considering upper bounds on durations, with the assumption that when an action happens to be executed more quickly, the plan will still succeed. However, this  assumption is often false: If we finish cooking too early, the dinner will be cold before everyone is ready to eat. 

    Using Simple Temporal Networks with Uncertainty (STNU), a planner can correctly take both lower and upper duration bounds into  account. It must then verify that the plans it generates are executable regardless of the actual outcomes of the uncertain durations. This is captured by the property of dynamic controllability (DC), which should be verified incrementally during plan generation. 

    Recently a new incremental algorithm for verifying dynamic controllability was proposed: EfficiantIDC, which can verify if an STNU that is DC remains DC after the addition or tightening of a constraint (corresponding to a new action being added to a plan). The algorithm was shown to have a worst case complexity of O(n4) for each addition or tightening. This can be amortized over the construction of a whole STNU for an amortized complexity in O(n3). In this paper we improve the EfficientIDC algorithm in a way that prevents it from having to reprocess nodes. This improvement leads to a lower worst case complexity in O(n3).

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  • 136.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Incremental Dynamic Controllability in Cubic Worst-Case Time2014In: Proceedings of the 21st International Symposium on Temporal Representation and Reasoning (TIME) / [ed] Cesta, A; Combi, C; Laroussinie, F, IEEE Computer Society Digital Library, 2014, p. 17-26Conference paper (Refereed)
    Abstract [en]

    It is generally hard to predict the exact duration of an action. The uncertainty in the duration is often modeled in temporal planning by the use of upper bounds on durations, with the assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false: If we finish cooking too early, the dinner will be cold before everyone is ready to eat. Simple Temporal Problems with Uncertainty (STPUs) allow us to model such situations. An STPU-based planner must verify that the plans it generates are executable, captured by the property of dynamic controllability. The EfficientIDC (EIDC) algorithm can do this incrementally during planning, with an amortized complexity per step of $O(n^3)$ but a worst-case complexity per step of $O(n^4)$. In this paper we show that the worst-case run-time of EIDC does occur, leading to repeated reprocessing of nodes in the STPU while verifying the dynamic controllability property. We present a new version of the algorithm, called EIDC2, which through optimal ordering of nodes avoids any need for reprocessing. This gives EIDC2 a strictly lower worst-case run-time, making it the fastest known algorithm for incrementally verifying dynamic controllability of STPUs.

  • 137.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, Department of Computer and Information Science, UASTECH - Autonomous Unmanned Aircraft Systems Technologies. Linköping University, The Institute of Technology.
    Incremental Dynamic Controllability Revisited2013In: Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS), AAAI Press, 2013Conference paper (Refereed)
    Abstract [en]

    Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are determined by nature, as is often the case for actions in planning. As such networks are generated it is essential to verify that they are dynamically controllable – executable regardless of the outcomes of uncontrollable durations – and to convert them to a dispatchable form. The previously published FastIDC algorithm achieves this incrementally and can therefore be used efficiently during plan construction. In this paper we show that FastIDC is not sound when new constraints are added, sometimes labeling networks as dynamically controllable when they are not. We analyze the algorithm, pinpoint the cause, and show how the algorithm can be modified to correctly detect uncontrollable networks.

  • 138.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters2018In: Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS) / [ed] Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan, Palo Alto, California USA: AAAI Press, 2018, p. 180-189Conference paper (Refereed)
    Abstract [en]

    We consider a general and industrially motivated class of planning problems involving a combination of requirements that can be essential to autonomous robotic systems planning to act in the real world: Support for temporal uncertainty where nature determines the eventual duration of an action, resource consumption with a non-linear relationship to durations, and the need to select appropriate values for control parameters that affect time requirements and resource usage. To this end, an existing planner is extended with support for Simple Temporal Networks with Uncertainty, Timed Initial Literals, and temporal coverage goals. Control parameters are lifted from the main combinatorial planning problem into a constraint satisfaction problem that connects them to resource usage. Constraint processing is then integrated and interleaved with verification of temporal feasibility, using projections for partial temporal awareness in the constraint solver.

  • 139.
    Nilsson, Mikael
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Revisiting Classical Dynamic Controllability: A Tighter Complexity Analysis2015In: Agents and Artificial Intelligence: 6th International Conference, ICAART 2014, Angers, France, March 6–8, 2014, Revised Selected Papers / [ed] Béatrice Duval; Jaap van den Herik; Stephane Loiseau; Joaquim Filipe, Springer, 2015, Vol. 8946, p. 243-261Conference paper (Refereed)
    Abstract [en]

    Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning.  It is essential to verify that such networks are dynamically controllable (DC) -- executable regardless of the outcomes of uncontrollable durations -- and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original, classical, verification algorithm. This algorithm is the entry level algorithm for DC verification, based on a less complex and more intuitive theory than subsequent algorithms. We show that with a small modification the algorithm is transformed from pseudo-polynomial to O(n4) which makes it still useful.  We also discuss a change reducing the amount of work performed by the algorithm.

  • 140.
    Olofsson, Jonatan
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Towards Autonomous Landing of a Quadrotorusing Monocular SLAM Techniques2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Use of Unmanned Aerial Vehicles have seen enormous growth in recent years due to the advances in related scientific and technological fields. This fact combined with decreasing costs of using UAVs enables their use in new application areas. Many of these areas are suitable for miniature scale UAVs - Micro Air Vehicles(MAV) - which have the added advantage of portability and ease of deployment. One of the main functionalities necessary for successful MAV deployment in real-world applications is autonomous landing. Landing puts particularly high requirements on positioning accuracy, especially in indoor confined environments where the common global positioning technology is unavailable. For that reason using an additional sensor, such as a camera, is beneficial. In this thesis, a set of technologies for achieving autonomous landing is developed and evaluated. In particular, state estimation based on monocular vision SLAM techniques is fused with data from onboard sensors. This is then used as the basis for nonlinear adaptive control as well trajectory generation for a simple landing procedure. These components are connected using a new proposed framework for robotic development. The proposed system has been fully implemented and tested in a simulated environment and validated using recorded data. Basic autonomous landing was performed in simulation and the result suggests that the proposed system is a viable solution for achieving a fully autonomous landing of a quadrotor.

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  • 141.
    Petersen, Karen
    et al.
    Technical University Darmstadt, Germany.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    von Stryk, Oskar
    Technical University Darmstadt, Germany.
    Fast Task-Sequence Allocation for Heterogeneous Robot Teams with a Human in the Loop2013In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), IEEE , 2013, p. 1648-1655Conference paper (Refereed)
    Abstract [en]

    Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e.g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art Mixed Integer Linear Programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision. 

  • 142.
    Pogulis, Jakob
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Testramverk för distribuerade system2013Independent thesis Basic level (degree of Bachelor), 10,5 credits / 16 HE creditsStudent thesis
    Abstract [en]

    When developing software that is meant to be distributed over several different computers and several different networks while still working together against a common goal there is a challenge in testing how updates within a single component will affect the system as a whole. Even if the performance of that specific component increases that is no guarantee for the increased performance of the entire system. Traditional methods of testing software becomes both hard and tedious when several different machines has to be involved for a single test and all of those machines has to be synchronized as well.This thesis has resulted in an exemplary application suite for testing distributed software. The thesis describes the method used for implementation as well as a description of the actual application suite that was developed. During the development several important factors and improvements for such a system was identified, which are described at the end of the thesis even though some of them never made it into the actual implementation. The implemented application suite could be used as a base when developing a more complete system in order to distribute tests and applications that has to run in a synchronized manner with the ability to report the results of each individual component.

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    LIU-IDA-LITH-EX-G--13-010--SE
  • 143.
    Präntare, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Simultaneous coalition formation and task assignment in a real-time strategy game2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis we present an algorithm that is designed to improve the collaborative capabilities of agents that operate in real-time multi-agent systems. Furthermore, we study the coalition formation and task assignment problems in the context of real-time strategy games. More specifically, we design and present a novel anytime algorithm for multi-agent cooperation that efficiently solves the simultaneous coalition formation and assignment problem, in which disjoint coalitions are formed and assigned to independent tasks simultaneously. This problem, that we denote the problem of collaboration formation, is a combinatorial optimization problem that has many real-world applications, including assigning disjoint groups of workers to regions or tasks, and forming cross-functional teams aimed at solving specific problems.

    The algorithm's performance is evaluated using randomized artificial problems sets of varying complexity and distribution, and also using Europa Universalis 4 – a commercial strategy game in which agents need to cooperate in order to effectively achieve their goals. The agents in such games are expected to decide on actions in real-time, and it is a difficult task to coordinate them. Our algorithm, however, solves the coordination problem in a structured manner.

    The results from the artificial problem sets demonstrates that our algorithm efficiently solves the problem of collaboration formation, and does so by automatically discarding suboptimal parts of the search space. For instance, in the easiest artificial problem sets with 12 agents and 8 tasks, our algorithm managed to find optimal solutions after only evaluating approximately 0.000003% of the possible solutions. In the hardest of the problem sets with 12 agents and 8 tasks, our algorithm managed to find a 80% efficient solution after only evaluating approximately 0.000006% of the possible solutions.

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    fulltext
  • 144.
    Präntare, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    An anytime algorithm for optimal simultaneous coalition structure generation and assignment2020In: Autonomous Agents and Multi-Agent Systems, ISSN 1387-2532, E-ISSN 1573-7454, Vol. 34, no 1, article id 29Article in journal (Refereed)
    Abstract [en]

    An important research problem in artificial intelligence is how to organize multiple agents, and coordinate them, so that they can work together to solve problems. Coordinating agents in a multi-agent system can significantly affect the systems performance-the agents can, in many instances, be organized so that they can solve tasks more efficiently, and consequently benefit collectively and individually. Central to this endeavor is coalition formation-the process by which heterogeneous agents organize and form disjoint groups (coalitions). Coalition formation often involves finding a coalition structure (an exhaustive set of disjoint coalitions) that maximizes the systems potential performance (e.g., social welfare) through coalition structure generation. However, coalition structure generation typically has no notion of goals. In cooperative settings, where coordination of multiple coalitions is important, this may generate suboptimal teams for achieving and accomplishing the tasks and goals at hand. With this in mind, we consider simultaneously generating coalitions of agents and assigning the coalitions to independent alternatives (e.g., tasks/goals), and present an anytime algorithm for the simultaneous coalition structure generation and assignment problem. This combinatorial optimization problem hasmany real-world applications, including forming goal-oriented teams. To evaluate the presented algorithms performance, we present five methods for synthetic problem set generation, and benchmark the algorithm against the industry-grade solver CPLEXusing randomized data sets of varying distribution and complexity. To test its anytime-performance, we compare the quality of its interim solutions against those generated by a greedy algorithm and pure random search. Finally, we also apply the algorithm to solve the problem of assigning agents to regions in a major commercial strategy game, and show that it can be used in game-playing to coordinate smaller sets of agents in real-time.

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    fulltext
  • 145.
    Präntare, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    An Anytime Algorithm for Simultaneous Coalition Structure Generation and Assignment2018In: PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings / [ed] Tim Miller, Nir Oren, Yuko Sakurai, Itsuki Noda, Bastin Tony Roy Savarimuthu and Tran Cao Son, Cham, 2018, Vol. 11224, p. 158-174Conference paper (Refereed)
    Abstract [en]

    A fundamental problem in artificial intelligence is how to organize and coordinate agents to improve their performance and skills. In this paper, we consider simultaneously generating coalitions of agents and assigning the coalitions to independent tasks, and present an anytime algorithm for the simultaneous coalition structure generation and assignment problem. This optimization problem has many real-world applications, including forming goal-oriented teams of agents. To evaluate the algorithm’s performance, we extend established methods for synthetic problem set generation, and benchmark the algorithm against CPLEX using randomized data sets of varying distribution and complexity. We also apply the algorithm to solve the problem of assigning agents to regions in a major commercial strategy game, and show that the algorithm can be utilized in game-playing to coordinate smaller sets of agents in real-time.

  • 146.
    Präntare, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Ragnemalm, Ingemar
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    An Algorithm for Simultaneous Coalition Structure Generation and Task Assignment2017In: PRIMA 2017: Principles and Practice of Multi-Agent Systems 20th International Conference, Nice, France, October 30 – November 3, 2017, Proceedings / [ed] Bo An, Ana Bazzan, João Leite, Serena Villata and Leendert van der Torre, Cham: Springer, 2017, Vol. 10621, p. 514-522Conference paper (Refereed)
    Abstract [en]

    Groups of agents in multi-agent systems may have to cooperate to solve tasks efficiently, and coordinating such groups is an important problem in the field of artificial intelligence. In this paper, we consider the problem of forming disjoint coalitions and assigning them to independent tasks simultaneously, and present an anytime algorithm that efficiently solves the simultaneous coalition structure generation and task assignment problem. This NP-complete combinatorial optimization problem has many real-world applications, including forming cross-functional teams aimed at solving tasks. To evaluate the algorithm's performance, we extend established methods for synthetic problem set generation, and benchmark the algorithm using randomized data sets of varying distribution and complexity. Our results show that the presented algorithm efficiently finds optimal solutions, and generates high quality solutions when interrupted prior to finishing an exhaustive search. Additionally, we apply the algorithm to solve the problem of assigning agents to regions in a commercial computer-based strategy game, and empirically show that our algorithm can significantly improve the coordination and computational efficiency of agents in a real-time multi-agent system.

  • 147.
    Quang-Thuy, Ha
    et al.
    Vietnam National University, Xuan Thuy, Hanoi.
    Thi-Lan-Giao, Hoang
    Hue University, Nguyen Hue, Hue city, Vietnam .
    Nguyen, Linh Anh
    University of Warsaw, Banacha, Poland .
    Hung-Son, Nguyen
    University of Warsaw, Banacha, Poland .
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Thanh-Luong, Tran
    Hue University, Nguyen Hue, Hue city, Vietnam .
    A Bisimulation-based Method of Concept Learning for Knowledge Bases in Description Logics2012In: SoICT 2012 - 3rd International Symposium on Information and Communication Technology, ACM Press, 2012, p. 241-249Conference paper (Refereed)
    Abstract [en]

    We develop the first bisimulation-based method of concept learning, called BBCL, for knowledge bases in description logics (DLs). Our method is formulated for a large class of useful DLs, with well-known DLs like ALC, SHIQ, SHOIQ, SROIQ. As bisimulation is the notion for characterizing indis-cernibility of objects in DLs, our method is natural and very promising.

  • 148.
    Quang-Thuy, Ha
    et al.
    Vietnam National University, Hanoi.
    Thi-Lan-Giao, Hoang
    Hue University, Hue city, Vietnam.
    Nguyen, Linh Anh
    University of Warsaw, Poland.
    Nguyen, Hung Son
    University of Warsaw, Poland.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Thanh-Luong, Tran
    Hue University, Hue city, Vietnam.
    Concept Learning for Description Logic-based Information Systems2012In: KSE 2012 - International Conference on Knowledge and Systems Engineering, IEEE Computer Society, 2012, p. 65-73Conference paper (Refereed)
  • 149.
    Rudol, Piotr
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Bridging Reactive and Control Architectural Layers for Cooperative Missions Using VTOL Platforms2017In: 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), IEEE , 2017, p. 21-32Conference paper (Refereed)
    Abstract [en]

    In this paper we address the issue of connecting abstract task definitions at a mission level with control functionalities for the purpose of performing autonomous robotic missions using multiple heterogenous platforms. The heterogeneity is handled by the use of a common vocabulary which consists of parametrized tasks such as fly-to, take-off, scan-area, or land. Each of the platforms participating in a mission supports a subset of the tasks by providing their platform-specific implementations. This paper presents a detailed description of an approach for implementing such platform-specific tasks. It is achieved using a flight-command based interface with setpoint generation abstraction layer for vertical take-off and landing platforms. We show that by using this highly expressive and easily parametrizable way of specifying and executing flight behaviors it is straightforward to implement a wide range of tasks. We describe the method in the context of a previously described robotics architecture which includes mission delegation and execution system based on a task specification language. We present results of an experimental flight using the proposed method.

  • 150.
    Rudol, Piotr
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Bridging the mission-control gap: A flight command layer for mediating flight behaviours and continuous control2016In: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 304-311Conference paper (Refereed)
    Abstract [en]

    The use of UAVs, in particular, micro VTOL UAVs, is becoming prevalent in emergency rescue and security applications, among others. In these applications, the platforms are tightly coupled to the human users and these applications require great flexibility in the interaction between the platforms and such users. During operation, one continually switches between manual, semi-autonomous and autonomous operation, often re-parameterising, breaking in, pausing, and resuming missions. One is in continual need of modifying existing elementary actions and behaviours such as FlyTo and TrackObject, and seamlessly switching between such operations. This paper proposes a flight command and setpoint abstraction layer that serves as an interface between continuous control and higher level elementary flight actions and behaviours. Introduction of such a layer into an architecture offers a versatile and flexible means of defining flight behaviours and dynamically parameterising them in the field, in particular where human users are involved. The system proposed is implemented in prototype and the paper provides experimental validation of the use and need for such abstractions in system architectures.

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