AAAI 2026technical0 citations
Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics
Yang You, Alex Schutz, Zhikun Li, Bruno Lacerda, Robert Skilton, Nick Hawes
Abstract
Many high-level multi-agent planning problems, such as multi-robot navigation and path planning, can be modeled with deterministic actions and observations. In this work, we focus on such domains and introduce the class of Deterministic Decentralized POMDPs (Det-Dec-POMDPs)—a subclass of Dec-POMDPs with deterministic transitions and observations given the state and joint actions. We then propose a practical solver, Iterative Deterministic POMDP Planning (IDPP), based on the classic Joint Equilibrium Search for Policies framework, specifically optimized to handle large-scale Det-Dec-POMDPs that existing Dec-POMDP solvers cannot handle efficiently.
BibTeX
@inproceedings{aaai2026_scalablesolution,
title = {Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics},
author = {Yang You and Alex Schutz and Zhikun Li and Bruno Lacerda and Robert Skilton and Nick Hawes},
booktitle = {AAAI 2026},
year = {2026}
}