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

arXiv 2109.08755 ↗First posted 17 Sep 2021cs.AIcited by 4

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Abstract (arXiv)

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 N-1 fixed FSCs into an infinite-horizon POMDP whose solution is an Nth 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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 4 of its 26 references that are in the map. First posted on arXiv 17 Sep 2021.

Builds on

4 of 26 references.

References · 4

  1. 2013The Complexity of Decentralized Control of Markov Decision Processescited by 231
  2. 2013Solving POMDPs by Searching the Space of Finite Policiescited by 26
  3. 2013Solving POMDPs by Searching in Policy Spacecited by 13
  4. 2014Policy Iteration for Decentralized Control of Markov Decision Processescited by 11

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4 papers.