Reactive Reinforcement Learning in Asynchronous Environments

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 tha...

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Bibliographische Detailangaben
Veröffentlicht in:Front Robot AI
Hauptverfasser: Travnik, Jaden B., Mathewson, Kory W., Sutton, Richard S., Pilarski, Patrick M.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2018
Schlagworte:
Robotics and AI
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7805616/
https://ncbi.nlm.nih.gov/pubmed/33500958
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frobt.2018.00079
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