Reactive Reinforcement Learning in Asynchronous Environments
Reactive Reinforcement Learning in Asynchronous Environments
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
The relationship between a reinforcement learning (RL) agent and an asynchronous environment is often ignored. Frequently used models of the interaction between an agent and its environment, such as Markov Decision Processes (MDP) or Semi-Markov Decision Processes (SMDP), do not capture the fact that, in an asynchronous environment, the state of th...
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Full title
Reactive Reinforcement Learning in Asynchronous Environments
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TN_cdi_proquest_journals_2073892549
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2073892549
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E-ISSN
2331-8422
DOI
10.48550/arxiv.1802.06139
