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Exploiting Fully Observable and Deterministic Structures in Goal POMDPs
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology. (APD)
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology. (APD)ORCID iD: 0000-0002-5500-8494
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.
2013 (English)In: Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS) / [ed] Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini, AAAI Press, 2013, 242-250 p.Conference paper, Presentation (Refereed)
Abstract [en]

When parts of the states in a goal POMDP are fully observable and some actions are deterministic it is possibleto take advantage of these properties to efficiently generate approximate solutions. Actions that deterministically affect the fully observable component of the world state can be abstracted away and combined into macro actions, permitting a planner to converge more quickly. This processing can be separated from the main search procedure, allowing us to leverage existing POMDP solvers. Theoretical results show how a POMDP can be analyzed to identify the exploitable properties and formal guarantees are provided showing that the use of macro actions preserves solvability. The efficiency of the method is demonstrated with examples when used in combination with existing POMDP solvers.

Place, publisher, year, edition, pages
AAAI Press, 2013. 242-250 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-88637ISBN: 978-1-57735-609-7OAI: oai:DiVA.org:liu-88637DiVA: diva2:605391
Conference
23rd International Conference on Automated Planning and Scheduling (ICAPS 2013), 10-14 June 2013, Rom, Italy
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2016-05-31Bibliographically approved
In thesis
1. Troubleshooting Trucks: Automated Planning and Diagnosis
Open this publication in new window or tab >>Troubleshooting Trucks: Automated Planning and Diagnosis
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Felsökning av lastbilar : automatiserad planering och diagnos
Abstract [en]

This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of which actions to take in order to solve the problem such that the expected cost of restoring the vehicle is low. To achieve this, such a system must be capable of solving two problems: the diagnosis problem of finding which the possible faults are and the decision problem of deciding which action should be taken.

The diagnosis problem has been approached using Bayesian network models. Frameworks have been developed for the case when the vehicle is in the workshop only and for remote diagnosis when the vehicle is monitored during longer periods of time.

The decision problem has been solved by creating planners that select actions such that the expected cost of repairing the vehicle is minimized. New methods, algorithms, and models have been developed for improving the performance of the planner.

The theory developed has been evaluated on models of an auxiliary braking system, a fuel injection system, and an engine temperature control and monitoring system.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 79 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1691
Keyword
automated planning, diagnosis, troubleshooting, automotive systems, Bayesian networks, Markov decision-processes
National Category
Computer Systems
Identifiers
urn:nbn:se:liu:diva-119445 (URN)10.3384/diss.diva-119445 (DOI)978-91-7685-993-3 (print) (ISBN)
Public defence
2015-10-16, Visionen, Hus B, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
VINNOVA, 2010-02864
Available from: 2015-09-23 Created: 2015-06-17 Last updated: 2015-10-12Bibliographically approved

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