DePAint: a decentralized safe multi-agent reinforcement learning algorithm considering peak and aver...
DePAint: a decentralized safe multi-agent reinforcement learning algorithm considering peak and average constraints
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Publisher
New York: Springer US
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Language
English
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Publisher
New York: Springer US
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Scope and Contents
Contents
The domain of safe multi-agent reinforcement learning (MARL), despite its potential applications in areas ranging from drone delivery and vehicle automation to the development of zero-energy communities, remains relatively unexplored. The primary challenge involves training agents to learn optimal policies that maximize rewards while adhering to st...
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Full title
DePAint: a decentralized safe multi-agent reinforcement learning algorithm considering peak and average constraints
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Author / Creator
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Record Identifier
TN_cdi_proquest_journals_3068494453
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3068494453
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ISSN
0924-669X
E-ISSN
1573-7497
DOI
10.1007/s10489-024-05433-x
