Decision theoretic behavior composition

Yadav, N and Sardina, S 2011, 'Decision theoretic behavior composition', in Tumer, Yolum, Sonenberg and Stone (ed.) Proceedings of 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, 2-6 May 2011, pp. 575-582.


Document type: Conference Paper
Collection: Conference Papers

Title Decision theoretic behavior composition
Author(s) Yadav, N
Sardina, S
Year 2011
Conference name 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011)
Conference location Taipei, Taiwan
Conference dates 2-6 May 2011
Proceedings title Proceedings of 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011)
Editor(s) Tumer, Yolum, Sonenberg and Stone
Publisher The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Place of publication United States
Start page 575
End page 582
Total pages 8
Abstract The behavior composition problem involves realizing a virtual target behavior (i.e., the desired module) by suitably coordinating the execution of a set of partially controllable available components (e.g., agents, devices, processes, etc.) running in a shared partially predictable environment. All existing approaches to such problem have been framed within strict uncertainty settings. In this work, we propose a framework for automatic behavior composition which allows the seamless integration of classical behavior composition with decision-theoretic reasoning. Specifically, we consider the problem of maximizing the 'expected realizability' of the target behavior in settings where the uncertainty can be quantified. Unlike previous proposals, the approach developed here is able to (better) deal with instances that do not accept 'exact' solutions, thus yielding a more practical account for real domains. Moreover, it is provably strictly more general than the classical composition framework. Besides formally defining the problem and what counts as a solution, we show how a decision-theoretic composition problem can be solved by reducing it to the problem of finding an optimal policy in a Markov decision process.
Subjects Adaptive Agents and Intelligent Robotics
Keyword(s) Behavior composition
decision theory
synthesis
Copyright notice Copyrigh © 2011, International Foundation for Autonomous Agents and Multiagent Systems
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