DocumentCode
2024514
Title
An application in RoboCup combining Q-learning with adversarial planning
Author
Yao, Jinyi ; Chen, Jiang ; Sun, Zengqi
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
1
fYear
2002
fDate
2002
Firstpage
496
Abstract
RoboCup is a standard problem so that various theories, algorithms and architectures can be evaluated. Behavior learning for complex tasks is also an important research area in RoboCup. In this paper, we present a new approach to solve the kick problem in RoboCup Simulation, which combines Q-learning with online adversarial planning. This method not only achieves satisfactory learning effect, but also solves the adversary kick problem to some extends.
Keywords
heuristic programming; learning (artificial intelligence); mobile robots; multi-robot systems; planning (artificial intelligence); search problems; Q-Learning; RoboCup; adversarial planning; heuristic search; kick problem; learning; Application software; Automatic control; Automation; Computational modeling; Computer architecture; Computer science; Intelligent systems; Laboratories; Sun; Technology planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN
0-7803-7268-9
Type
conf
DOI
10.1109/WCICA.2002.1022159
Filename
1022159
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