Publications• Sorted by Date • Classified by Publication Type • Classified by Research Category • Multiagent Planning under Uncertainty with Stochastic Communication DelaysMatthijs T. J. Spaan, Frans A. Oliehoek, and Nikos Vlassis. Multiagent Planning under Uncertainty with Stochastic Communication Delays. In Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, pp. 338–345, September 2008. DownloadAbstractWe consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). By communicating their local observations before they take actions, the agents synchronize their knowledge of the environment, and the planning problem reduces to a centralized POMDP. As such, relying on communication significantly reduces the complexity of planning. In the real world however, such communication might fail temporarily. We present a step towards more realistic communication models for Dec-POMDPs by proposing a model that: (1) allows that communication might be delayed by one or more stages, and (2) explicitly reasons about the probability of successful communication in the future. For our model, we discuss how to efficiently compute an (approximate) value function and corresponding policies, and we demonstrate our theoretical results with encouraging experiments. BibTeX Entry@InProceedings{Spaan08ICAPS, author = {Matthijs T. J. Spaan and Frans A. Oliehoek and Nikos Vlassis}, title = {Multiagent Planning under Uncertainty with Stochastic Communication Delays}, booktitle = ICAPS08, month = sep, year = 2008, pages = {338--345}, url = {https://www.aaai.org/Papers/ICAPS/2008/ICAPS08-042.pdf}, abstract = { We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). By communicating their local observations before they take actions, the agents synchronize their knowledge of the environment, and the planning problem reduces to a centralized POMDP. As such, relying on communication significantly reduces the complexity of planning. In the real world however, such communication might fail temporarily. We present a step towards more realistic communication models for Dec-POMDPs by proposing a model that: (1) allows that communication might be delayed by one or more stages, and (2) explicitly reasons about the probability of successful communication in the future. For our model, we discuss how to efficiently compute an (approximate) value function and corresponding policies, and we demonstrate our theoretical results with encouraging experiments. } }
Generated by
bib2html.pl
(written by Patrick Riley) on
Mon Oct 07, 2024 14:17:04 UTC |