Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems: Part 1—Fundamentals and Applications in Games, Robotics and Natural Language Processing

Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems: Part 1—Fundamentals and Applications in Games, Robotics and Natural Language Processing

The first part of a two-part series of papers provides a survey on recent advances in Deep Reinforcement Learning (DRL) applications for solving partially observable Markov decision processes (POMDP) problems. Reinforcement Learning (RL) is an approach to simulate the human’s natural learning proces...

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Bibliographic Details
Main Authors: Xuanchen Xiang, Simon Foo
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Machine Learning and Knowledge Extraction
Subjects:
reinforcement learning
deep reinforcement learning
Markov decision process
partially observable Markov decision process
Online Access:https://www.mdpi.com/2504-4990/3/3/29

Internet

https://www.mdpi.com/2504-4990/3/3/29

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