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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Detalles Bibliográficos
Autores principales: Travnik, Jaden B., Mathewson, Kory W., Sutton, Richard S., Pilarski, Patrick M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Robotics and AI
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805616/
https://www.ncbi.nlm.nih.gov/pubmed/33500958
http://dx.doi.org/10.3389/frobt.2018.00079

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805616/
https://www.ncbi.nlm.nih.gov/pubmed/33500958
http://dx.doi.org/10.3389/frobt.2018.00079

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