Network distributed POMDP with communication

Yuki Iwanari, Yuichi Yabu, Makoto Tasaki, Makoto Yokoo

研究成果: Chapter in Book/Report/Conference proceedingConference contribution


While Distributed POMDPs have become popular for modeling multiagent systems in uncertain domains, it is the Network Distributed POMDPs (ND-POMDPs) model that has begun to scale-up the number of agents. The ND-POMDPs can utilize the locality in agents' interactions. However, prior work in ND-POMDPs has failed to address communication. Without communication, the size of a local policy at each agent within the ND-POMDPs grows exponentially in the time horizon. To overcome this problem, we extend existing algorithms so that agents periodically communicate their observation and action histories with each other. After communication, agents can start from new synchronized belief state. Thus, we can avoid the exponential growth in the size of local policies at agents. Furthermore, we introduce an idea that is similar the Point-based Value Iteration algorithm to approximate the value function with a fixed number of representative points. Our experimental results show that we can obtain much longer policies than isting algorithms as long as the interval between communications is small.

ホスト出版物のタイトルNew Frontiers in Artificial Intelligence - JSAI 2008 Conference and Workshops, Revised Selected Papers
出版ステータス出版済み - 7 23 2009
イベントJSAI 2008 Conference and Workshops: New Frontiers in Artificial Intelligence - Asahikawa, 日本
継続期間: 6 11 20086 13 2008


名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5447 LNAI


その他JSAI 2008 Conference and Workshops: New Frontiers in Artificial Intelligence

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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