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• W2924816077 abstract "Decentralized partially observable Markov decision processes (Dec-POMDPs) are general models for decentralized multi-agent decision making under uncertainty. However, they typically model a problem at a low level of granularity, where each agent's actions are primitive operations lasting exactly one time step. We address the case where each agent has macro-actions: temporally extended actions that may require different amounts of time to execute. We model macro-actions as options in a Dec-POMDP, focusing on actions that depend only on information directly available to the agent during execution. Therefore, we model systems where coordination decisions only occur at the level of deciding which macro-actions to execute. The core technical difficulty in this setting is that the options chosen by each agent no longer terminate at the same time. We extend three leading Dec-POMDP algorithms for policy generation to the macro-action case, and demonstrate their effectiveness in both standard benchmarks and a multi-robot coordination problem. The results show that our new algorithms retain agent coordination while allowing high-quality solutions to be generated for significantly longer horizons and larger state-spaces than previous Dec-POMDP methods. Furthermore, in the multi-robot domain, we show that, in contrast to most existing methods that are specialized to a particular problem class, our approach can synthesize control policies that exploit opportunities for coordination while balancing uncertainty, sensor information, and information about other agents." @default.
• W2924816077 created "2019-04-01" @default.
• W2924816077 creator A5011665886 @default.
• W2924816077 creator A5012862284 @default.
• W2924816077 creator A5033129735 @default.
• W2924816077 creator A5078124517 @default.
• W2924816077 date "2019-03-25" @default.
• W2924816077 modified "2023-10-16" @default.
• W2924816077 title "Modeling and Planning with Macro-Actions in Decentralized POMDPs" @default.
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• W2924816077 doi "https://doi.org/10.1613/jair.1.11418" @default.
• W2924816077 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6814204" @default.
• W2924816077 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31656393" @default.
• W2924816077 hasPublicationYear "2019" @default.
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