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Research on Robocup Simulation System and Program Design Based on Reinforcement Learning

Author: GaoYong
Tutor: ZengQingJun
School: Jiangsu University of Science and Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Robot Soccer RoboCup Multi-Agent Reinforcement Learning Minimax Q- learning algorithm
CLC: TP242
Type: Master's thesis
Year: 2011
Downloads: 44
Quote: 1
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Abstract


RoboCup provides a standard task to to promote distributed artificial intelligence and intelligent robotics , and related fields of research and development . RoboCup simulation game provides a fully distributed control , real-time asynchronous multi-agent environment , through this platform to test various theories , algorithms and Client architecture , in real-time asynchronous noisy environment to study the problem of multi-agent confrontation . The core technology of the robot soccer artificial intelligence technology, and its purpose is to make the machine has the wisdom of the people , like people aware environment , the ability to learn to the environment . Of this thesis is to study the the RoboCup simulation group game . Robot Soccer World Cup (RoboCup) The simulation group game in a standard computer environment . The game Soccer Server System is standard provided by the RoboCup Committee , various teams to prepare their respective Client program to simulate the actual football players participate in the competition . The paper first analyzes the the robot soccer RoboCup simulation system design and realization , and then focuses on the Amsterdam the UvA-Trilearn team of Client- system structure , program flow , based on program design , mainly include increasing the scenes strategy and evaluation function and other methods. Research on high-level strategy minimax Q- learning method based on the Markov decision process , the simulation results show that the method can solve the problems of confrontation between the agent . The main work of the thesis completed as follows : ( 1 ) to study the composition and operating principle of the system of the entire the RoboCup simulation game platform , which is the basis of the design RoboCup simulation team . (2) The basic operation of the study simulated soccer robots to analyze the characteristics of the operation . On this basis , the design action evaluation function and increase the scene processing strategy . (3) C program in linux platform designed to complete the simulation game client to write, debug and run . (4) of Markov decision processes and reinforcement learning algorithm design minimax - based Q- learning method , and its application in the shortest path problem and RoboCup . The simulation results show that the algorithm can solve the multi confrontation between Agent .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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