Abstract
A decentralised partially observable Markov decision problem (DecPOMDP) formalises collaborative multi-agent decision making. A solution to a DecPOMDP is a joint policy for the agents, fulfilling an optimality criterion such as maximum expected utility. A crux is that the problem is intractable regarding the number of agents. Inspired by lifted inference, this paper examines symmetries within the agent set for a potential tractability. Specifically, this paper contributes (i) specifications of counting and isomorphic symmetries, (ii) a compact encoding of symmetric DecPOMDPs as partitioned DecPOMDPs, and (iii) a formal analysis of complexity and tractability. This works allows tractability in terms of agent numbers and a new query type for isomorphic DecPOMDPs.
| Original language | English |
|---|---|
| Title of host publication | 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), Eindhoven, Netherlands, August 1-5, 2022 |
| Number of pages | 11 |
| Publication date | 2022 |
| Pages | 233-243 |
| Publication status | Published - 2022 |
| Event | UAI 2022: 38th Conference on Uncertainty in Artificial Intelligence - Eindhoven University of Technology , Eindhoven, Netherlands Duration: 01.08.2022 → 05.08.2022 https://www.auai.org/uai2022/ |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being -
SDG 4 Quality Education -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 12 Responsible Consumption and Production -
SDG 14 Life Below Water -
SDG 15 Life on Land
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
- Research Area: Intelligent Systems
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