Solving infinite-horizon Dec-POMDPs using Finite State Controllers within JESP
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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
- 2013The Complexity of Decentralized Control of Markov Decision Processescited by 231
- 2013Solving POMDPs by Searching the Space of Finite Policiescited by 26
- 2013Solving POMDPs by Searching in Policy Spacecited by 13
- 2014Policy Iteration for Decentralized Control of Markov Decision Processescited by 11
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Citing papers per year: 2023: 2; 2024: 0; 2025: 2.
4 papers.
- 2025Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics29 Aug 2025
- 2025Decentralized Planning Using Probabilistic Hyperproperties19 Feb 2025
- 2023Monte-Carlo Search for an Equilibrium in Dec-POMDPs19 May 2023
- 2023Robust Robot Planning for Human-Robot Collaboration27 Feb 2023