An Adaptive Strategy Selection Method With Reinforcement Learning for Robotic Soccer Games

An Adaptive Strategy Selection Method With Reinforcement Learning for Robotic Soccer Games

Robotic soccer games, which have become popular, require timely and precise decisionmaking in a dynamic environment. To address the problems of complexity in a critical situation, policy improvement in robotic soccer games must occur. This paper proposes an adaptive decisionmaking method that uses r...

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Bibliographic Details
Main Authors: Haobin Shi, Zhiqiang Lin, Kao-Shing Hwang, Shike Yang, Jialin Chen
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Robotic soccer
support vector machines
reinforcement learning
Q learning
Online Access:https://ieeexplore.ieee.org/document/8301430/

Internet

https://ieeexplore.ieee.org/document/8301430/

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