liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 16 of 16
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Doherty, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Kertes, Steven
    Stanford University.
    Magnusson, Martin
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Towards a logical analysis of biochemical pathways2004In: Proceedings of the 9th European Conference on Logics in Artificial Intelligence (JELIA) / [ed] José Júlio Alferes and João Alexandre Leite, Springer , 2004, Vol. 3229, p. 667-679Conference paper (Refereed)
    Abstract [en]

    Biochemical pathways or networks are generic representations used to model many different types of complex functional and physical interactions in biological systems. Models based on experimental results are often incomplete, e.g., reactions may be missing and only some products are observed. In such cases, one would like to reason about incomplete network representations and propose candidate hypotheses, which when represented as additional reactions, substrates, products, would complete the network and provide causal explanations for the existing observations. In this paper, we provide a logical model of biochemical pathways and show how abductive hypothesis generation may be used to provide additional information about incomplete pathways. Hypothesis generation is achieved using weakest and strongest necessary conditions which represent these incomplete biochemical pathways and explain observations about the functional and physical interactions being modeled. The techniques are demonstrated using metabolism and molecular synthesis examples.

  • 2.
    Doherty, Patrick
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Kertes, Steven
    Stanford University.
    Magnusson, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Szalas, Andrzej
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Towards a Logical Analysis of Biochemical Reactions (Extended abstract)2004In: Proceedings of the 16th European Conference on Artificial Intelligence (ECAI) / [ed] Ramon López de Mántaras, Lorenza Saitta, Amsterdam: IOS Press, 2004, p. 997-998Conference paper (Refereed)
    Abstract [en]

    We provide a logical model of biochemical reactions and show how hypothesis generation using weakest sufficient and strongest necessary conditions may be used to provide additional information in the context of an incomplete model of metabolic pathways.

  • 3.
    Doherty, Patrick
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Magnusson, Martin
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Approximate Databases: A support tool for approximate reasoning2006In: Journal of applied non-classical logics, ISSN 1166-3081, Vol. 16, no 1-2, p. 87-118Article in journal (Refereed)
    Abstract [en]

    This paper describes an experimental platform for approximate knowledge databases called the Approximate Knowledge Database (AKDB), based on a semantics inspired by rough sets. The implementation is based upon the use of a standard SQL database to store logical facts, augmented with several query interface layers implemented in JAVA through which extensional, intensional and local closed world nonmonotonic queries in the form of crisp or approximate logical formulas can be evaluated tractably. A graphical database design user interface is also provided which simplifies the design of databases, the entering of data and the construction of queries. The theory and semantics for AKDBs is presented in addition to application examples and details concerning the database implementation.

  • 4.
    Kvarnström, Jonas
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Magnusson, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    TALplanner in the Third International Planning Competition: Extensions and control rules2003In: The journal of artificial intelligence research, ISSN 1076-9757, E-ISSN 1943-5037, Vol. 20, p. 343-377Article in journal (Refereed)
    Abstract [en]

    TALplanner is a forward-chaining planner that relies on domain knowledge in the shape of temporal logic formulas in order to prune irrelevant parts of the search space. TALplanner recently participated in the third International Planning Competition, which had a clear emphasis on increasing the complexity of the problem domains being used as benchmark tests and the expressivity required to represent these domains in a planning system. Like many other planners, TALplanner had support for some but not all aspects of this increase in expressivity, and a number of changes to the planner were required. After a short introduction to TALplanner, this article describes some of the changes that were made before and during the competition. We also describe the process of introducing suitable domain knowledge for several of the competition domains.

  • 5.
    Magnusson, Martin
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Deductive Planning and Composite Actions in Temporal Action Logic2007Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Temporal Action Logic is a well established logical formalism for reasoning about action and change that has long been used as a formal specification language. Its first-order characterization and explicit time representation makes it a suitable target for automated theorem proving and the application of temporal constraint solvers. We introduce a translation from a subset of Temporal Action Logic to constraint logic programs that takes advantage of these characteristics to make the logic applicable, not just as a formal specification language, but in solving practical reasoning problems. Extensions are introduced that enable the generation of action sequences, thus paving the road for interesting applications in deductive planning. The use of qualitative temporal constraints makes it possible to follow a least commitment strategy and construct partially ordered plans. Furthermore, the logical language and logic program translation is extended with the notion of composite actions that can be used to formulate and execute scripted plans with conditional actions, non-deterministic choices, and loops. The resulting planner and reasoner is integrated with a graphical user interface in our autonomous helicopter research system and applied to logistics problems. Solution plans are synthesized together with monitoring constraints that trigger the generation of recovery actions in cases of execution failures.

  • 6.
    Magnusson, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Natural Language Understanding using Temporal Action Logic2006In: Proceedings of the Workshop on Knowledge and Reasoning for Language Processing (KRAQ), Stroudsburg, PA, USA: Association for Computational Linguistics , 2006, p. 26-Conference paper (Refereed)
    Abstract [en]

    We consider a logicist approach to natural language understanding based on the translation of a quasi-logical form into a temporal logic, explicitly constructed for the representation of action and change, and the subsequent reasoning about this semantic structure in the context of a background knowledge theory using automated theorem proving techniques. The approach is substantiated through a proof-of-concept question answering system implementation that uses a head-driven phrase structure grammar developed in the Linguistic Knowledge Builder to construct minimal recursion semantics structures which are translated into a Temporal Action Logic where both the SNARK automated theorem prover and the Allegro Prolog logic programming environment can be used for reasoning through an interchangeable compilation into first-order logic or logic programs respectively.

  • 7.
    Magnusson, Martin
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Deductive Planning with Inductive Loops2008In: Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR), Menlo Park, CA, USA: AAAI Press , 2008, p. 528-534Conference paper (Refereed)
    Abstract [en]

    Agents plan to achieve and maintain goals. Maintenance that requires continuous action excludes the representation of plans as finite sequences of actions. If there is no upper bound on the number of actions, a simple list of actions would be infinitely long. Instead, a compact representation requires some form of looping construct. We look at a specific temporally extended maintenance goal, multiple target video surveillance, and formalize it in Temporal Action Logic. The logic's representation of time as the natural numbers suggests using mathematical induction to deductively plan to satisfy temporally extended goals. Such planning makes use of a sound and useful, but incomplete, induction rule that compactly represents the solution as a recursive fixpoint formula. Two heuristic rules overcome the problem of identifying a sufficiently strong induction hypothesis and enable an automated solution to the surveillance problem that satisfies the goal indefinitely.

  • 8.
    Magnusson, Martin
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Deductive Planning with Temporal Constraints2007In: Commonsense 2007, the 8th International Symposium on Logical Formalizations of Commonsense Reasoning,2007, Menlo Park, CA, USA: AAAI Press , 2007Conference paper (Refereed)
    Abstract [en]

    Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

  • 9.
    Magnusson, Martin
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Deductive Planning with Temporal Constraints using TAL2006In: Proceedings of the International Symposium on Practical Cognitive Agents and Robots (PCAR), Claremont, Australia: UWA Press , 2006, p. 141-Conference paper (Refereed)
    Abstract [en]

    Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

  • 10.
    Magnusson, Martin
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Logical Agents for Language and Action2008In: 4th International Artificial Intelligence and Interactive Digital Entertainment Conference AIIDE 2008,2008, Menlo Park, CA, USA: AAAI Press , 2008Conference paper (Refereed)
  • 11.
    Magnusson, Martin
    et al.
    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, The Institute of Technology.
    Planning Speech Acts in a Logic of Action and Change2009In: The Swedish AI Society Workshop 2009, SAIS 2009 / [ed] Fredrik Heintz and Jonas Kvarnström, Linköping University Electronic Press, Linköpings universitet , 2009, p. 39-48Conference paper (Other academic)
    Abstract [en]

    Cooperation is a complex task that necessarily involves communication and reasoning about others’ intentions and beliefs. Multi-agent communication languages aid designers of cooperating robots through standardized speech acts, sometimes including a formal semantics. But a more direct approach would be to have the robots plan both regular and communicative actions themselves. We show how two robots with heterogeneous capabilities can autonomously decide to cooperate when faced with a task that would otherwise be impossible. Request and inform speech acts are formulated in the same first-order logic of action and change as is used for regular actions. This is made possible by treating the contents of communicative actions as quoted formulas of the same language. The robot agents then use a natural deduction theorem prover to generate cooperative plans for an example scenario by reasoning directly with the axioms of the theory.

  • 12.
    Magnusson, Martin
    et al.
    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, The Institute of Technology.
    Temporal Action Logic for Question Answering in an Adventure Game2008In: Artificial General Intelligence, AGI 2008, Amsterdam, Netherlands: IOS Press, 2008, p. 236-247Conference paper (Refereed)
    Abstract [en]

    Inhabiting the complex and dynamic environments of modern computer games with autonomous agents capable of intelligent timely behaviour is a significant research challenge. We illustrate this using Our own attempts to build a practical agent architecture on it logicist foundation. In the ANDI-Land adventure game concept players solve puzzles by eliciting information from computer characters through natural language question answering. While numerous challenges immediately presented themselves, they took on a form of concrete and accessible problems to solve, and we present some of our initial solutions. We conclude that games, due to their demand for human-like computer characters with robust and independent operation in large simulated worlds, might serve as excellent test beds for research towards artificial general intelligence.

  • 13.
    Magnusson, Martin
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Szalas, Andrzej
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    An Experimental Platform for Approximate Databases2005In: 3rd joint SAIS-SSL event on Artificial Intelligence and Learning Systems,2005, 2005, p. 124-Conference paper (Refereed)
  • 14.
    Magnusson, Martin
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. 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, The Institute of Technology.
    Abductive Reasoning with Filtered Circumscription2009In: Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change (NRAC), Sydney: UTSePress , 2009Conference paper (Refereed)
    Abstract [en]

    For logical artificial intelligence to be truly useful,its methods must scale to problems of realistic size.An interruptible algorithm enables a logical agentto act in a timely manner to the best of its knowledge,given its reasoning so far. This seems necessaryto avoid analysis paralysis, trying to thinkof every potentiality, however unlikely, beforehand.These considerations prompt us to look for alternativereasoning mechanisms for filtered circumscription,a nonmonotonic reasoning formalism usede.g. by Temporal Action Logic and Event Calculus.We generalize Ginsberg’s circumscriptive theoremprover and describe an interruptible theoremprover based on abduction that has been used tounify planning and reasoning in a logical agent architecture.

  • 15.
    Magnusson, Martin
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Landén, David
    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, The Institute of Technology.
    Logical Agents that Plan, Execute, and Monitor Communication2009In: Proceedings of the 2nd Workshop on Logic and the Simulation of Interaction and Reasoning (LSIR-2), 2009Conference paper (Refereed)
  • 16.
    Magnusson, Martin
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Landén, David
    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, The Institute of Technology.
    Planning, Executing, and Monitoring Communication in a Logic-Based Multi-Agent System2008In: ECAI 2008, Amsterdam, Netherlands: IOS Press, 2008, p. 933-934Conference paper (Refereed)
1 - 16 of 16
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf