English

Solving infinite-horizon Dec-POMDPs using Finite State Controllers within JESP

Artificial Intelligence 2021-09-21 v1

Abstract

This paper looks at solving collaborative planning problems formalized as Decentralized POMDPs (Dec-POMDPs) by searching for Nash equilibria, i.e., situations where each agent's policy is a best response to the other agents' (fixed) policies. While the Joint Equilibrium-based Search for Policies (JESP) algorithm does this in the finite-horizon setting relying on policy trees, we propose here to adapt it to infinite-horizon Dec-POMDPs by using finite state controller (FSC) policy representations. In this article, we (1) explain how to turn a Dec-POMDP with N1N-1 fixed FSCs into an infinite-horizon POMDP whose solution is an NthN^\text{th} agent best response; (2) propose a JESP variant, called \infJESP, using this to solve infinite-horizon Dec-POMDPs; (3) introduce heuristic initializations for JESP aiming at leading to good solutions; and (4) conduct experiments on state-of-the-art benchmark problems to evaluate our approach.

Cite

@article{arxiv.2109.08755,
  title  = {Solving infinite-horizon Dec-POMDPs using Finite State Controllers within JESP},
  author = {Yang You and Vincent Thomas and Francis Colas and Olivier Buffet},
  journal= {arXiv preprint arXiv:2109.08755},
  year   = {2021}
}

Comments

Extended version of ICTAI 2021 paper

R2 v1 2026-06-24T06:05:22.107Z