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Controller Compilation and Compression for Resource Constrained Applications

Grzes, Marek and Poupart, Pascal and Hoey, Jesse (2013) Controller Compilation and Compression for Resource Constrained Applications. In: Perny, Patrice and Pirlot, Marc and Tsoukias, Alexis, eds. Algorithmic Decision Theory Third International Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 193-207. ISBN 978-3-642-41574-6. E-ISBN 978-3-642-41575-3. (doi:10.1007/978-3-642-41575-3_15) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Abstract

Recent advances in planning techniques for partially observable Markov decision processes have focused on online search techniques and offline point-based value iteration. While these techniques allow practitioners to obtain policies for fairly large problems, they assume that a non-negligible amount of computation can be done between each decision point. In contrast, the recent proliferation of mobile and embedded devices has lead to a surge of applications that could benefit from state of the art planning techniques if they can operate under severe constraints on computational resources. To that effect, we describe two techniques to compile policies into controllers that can be executed by a mere table lookup at each decision point. The first approach compiles policies induced by a set of alpha vectors (such as those obtained by point-based techniques) into approximately equivalent controllers, while the second approach performs a simulation to compile arbitrary policies into approximately equivalent controllers. We also describe an approach to compress controllers by removing redundant and dominated nodes, often yielding smaller and yet better controllers. The compilation and compression techniques are demonstrated on benchmark problems as well as a mobile application to help Alzheimer patients to way-find.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-41575-3_15
Uncontrolled keywords: Energy-efficiency, Finite-state Controllers, Knowledge compilation, Markov decision processes, Mobile Applications, POMDPs
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Marek Grzes
Date Deposited: 26 May 2015 20:37 UTC
Last Modified: 15 Oct 2019 14:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48656 (The current URI for this page, for reference purposes)
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