Point-based backup for decentralized POMDPs: complexity and new algorithms

Decentralized POMDPs provide an expressive framework for sequential multi-agent decision making. Despite their high complexity, there has been significant progress in scaling up existing algorithms, largely due to the use of pointbased methods. Performing point-based backup is a fundamental operation in state-of-the-art algorithms. We show that even a single backup step in the multi-agent setting is NP-Complete. Despite this negative worst-case result, we present an efficient and scalable optimal algorithm as well as a principled approximation scheme. The optimal algorithm exploits recent advances in the weighted CSP literature to overcome the complexity of the backup operation. The polytime approximation scheme provides a constant factor approximation guarantee based on the number of belief points. In experiments on standard domains, the optimal approach provides significant speedup (up to 2 orders of magnitude) over the previous best optimal algorithm and is able to increase the num...

• Type: Conference
• Year: 2010
• Where: ATAL
• Authors: Akshat Kumar, Shlomo Zilberstein
• Keywords: Approximation Scheme, ATAL 2010, Intelligent Agents, Optimal Algorithm, Principled Approximation Scheme