On Markov Policies For Decentralized POMDPs

Jilles Steeve Dibangoye 1
1 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : This paper formulates the optimal decentralized control problem for a class of mathematical models in which the system to be controlled is characterized by a finite-state discrete-time Markov process. The states of this internal process are not directly observable by the agents; rather, they have available a set of observable outputs that are only probabilistically related to the internal state of the system. The paper demonstrates that, if there are only a finite number of control intervals remaining, then the optimal payoff function of a Markov policy is a piecewise-linear, convex function of the current observation probabilities of the internal partially observable Markov process. In addition, algorithms for utilizing this property to calculate either the optimal or an error-bounded Markov policy and payoff function for any finite horizon is outlined.
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Jilles Steeve Dibangoye. On Markov Policies For Decentralized POMDPs. [Research Report] RR-9202, INRIA Grenoble - Rhone-Alpes - CHROMA Team; CITI - CITI Centre of Innovation in Telecommunications and Integration of services; INSA Lyon. 2018. ⟨hal-01860060⟩

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