Výsledky vyhledávání

Introducing communication in Dis-POMDPs with locality of interaction

Autor: Pradeep Varakantham, Makoto Tasaki, Yuichi Yabu, Milind Tambe, Yuki Iwanari, Makoto Yokoo, Janusz Marecki

Publikováno v: IAT

The Networked Distributed POMDPs (ND-POMDPs) can model multiagent systems in uncertain domains and have begun to scale-up the number of agents. However, prior work in ND-POMDPs has failed to address communication. Without communication, the size of a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a0b4ebc3cb8a73b9604ddbefa9cea9c
https://doi.org/10.3233/wia-2010-0193

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Multiagent Planning with Trembling-Hand Perfect Equilibrium in Multiagent POMDPs

Autor: Yuichi Yabu, Atsushi Iwasaki, Makoto Yokoo

Publikováno v: Agent Computing and Multi-Agent Systems ISBN: 9783642016387
PRIMA

Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint policy is prohibitive, a Joint Equilibrium-based Search for Policies with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d017e1876f0fa7354a620e84fa097977
https://doi.org/10.1007/978-3-642-01639-4_2

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Network Distributed POMDP with Communication

Autor: Yuichi Yabu, Makoto Yokoo, Makoto Tasaki, Yuki Iwanari

Publikováno v: New Frontiers in Artificial Intelligence ISBN: 9783642006081
JSAI

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 agent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bda03cfb1fbeb111ed8f81efa476a07c
https://doi.org/10.1007/978-3-642-00609-8_4

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Letting loose a SPIDER on a network of POMDPs

Autor: Makoto Yokoo, Yuichi Yabu, Pradeep Varakantham, Janusz Marecki, Milind Tambe

Publikováno v: AAMAS

Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the significant complexity of solving distributed POMDPs, particularly as we sca

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::83169e53b40e59e87d5576b79e36ebaf
https://doi.org/10.1145/1329125.1329388

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