Network distributed POMDP with communication

Yuki Iwanari, Yuichi Yabu, Makoto Tasaki, Makoto Yokoo

Research output: 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.

Original languageEnglish
Title of host publicationNew Frontiers in Artificial Intelligence - JSAI 2008 Conference and Workshops, Revised Selected Papers
Number of pages13
Publication statusPublished - 2009
EventJSAI 2008 Conference and Workshops: New Frontiers in Artificial Intelligence - Asahikawa, Japan
Duration: Jun 11 2008Jun 13 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5447 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherJSAI 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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