Journal of Guangxi Normal University(Natural Science Edition) ›› 2010, Vol. 28 ›› Issue (3): 99-103.

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Improved Reinforcement Learning Algorithm and Its Application in RoboCup

CHENG Xian-yi1,2, ZHU Qian2   

  1. 1. College of Computer Science and Technology,Nantong University,Nantong Jiangsu 226019,China;
    2. College of Computer Science and Telecommunications Engineering,Jiangsu University, Zhenjiang Jiangsu 212013,China
  • Received:2010-05-13 Online:2010-09-20 Published:2023-02-06

Abstract: An improved algorithm based on CMAC (cerebella modelarticulation controller) and named DCMAC-AL is proposed.It uses advantage(λ) learning to calculate the state-action function,emphasizes the differences among action values and shuns action oscillation.It creates novel features based on Bellman error to improvethe adaption of CMAC.Besides,it provides a mathematic model for takeaway in RoboCup Soccer Simulation and experiment with DCMAC-AL.The results demonstrate thatDCMAC-AL outperforms advantage(λ) learning in regard to learning effort.

Key words: reinforcement learning, agent, RoboCup, CMAC

CLC Number: 

  • TP181
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