Journal of Beijing University of Posts and Telecommunications

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JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM

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Policy Estimation Error Analysis for Symmetrical MARL Problem in Communication Resource Scheduling

ZHANG Xin-ran, SUN Song-lin   

  1. 1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. Key Laboratory of Trustworthy Distributed Computing and Service(Ministry of Education), Beijing University of Posts and Telecommunications, Beijing 100876, China;
    3. National Engineering Laboratory for Mobile Network Security, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2018-06-20 Online:2019-04-28 Published:2019-04-28

Abstract: Considering multi-agent reinforcement learning (MARL) theory in communication resource scheduling scenario, the symmetrical MARL problem was proposed with definitions for three types of symmetry properties and analysis of policy estimation error. The policy estimation error theorem for strong symmetrical MARL was presented. Simulation results based on the admission control problem in wireless system were modeled by MARL, which testify the characteristics of policy estimation error for strong symmetrical MARL problems. It shows that using the MARL sub-problems with low computational complexity to estimate the original MARL problem with high computational complexity only brings small policy estimation error and deterioration of system performance.

Key words: reinforcement learning, symmetrical multi-agent reinforcement learning, policy estimation

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