Reactive Reinforcement Learning in Asynchronous Environments

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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Bibliographic Details
Main Authors: Jaden B. Travnik, Kory W. Mathewson, Richard S. Sutton, Patrick M. Pilarski
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Robotics and AI
Subjects:
reinforcement learning
asynchronous environments
resource-limited systems
reaction time
real-time machine learning
Online Access:https://www.frontiersin.org/article/10.3389/frobt.2018.00079/full

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https://www.frontiersin.org/article/10.3389/frobt.2018.00079/full

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