Title :
Reinforcement learning of player agents in RoboCup Soccer simulation
Author :
Sarje, Abhinav ; Chawre, Amit ; Nair, Shivashankar B.
Author_Institution :
Center for Dev. of Telematics, Bangalore, India
Abstract :
Multiagent systems have emerged as an active sub field of artificial intelligence. Machine learning techniques have played a significant role by handling the inherent complexity of such systems. Robotic Soccer is a typical multiagent system, wherein the challenge is to develop and hone the skills of the agents that take part in the game. For an in-depth and sophisticated understanding of the game, soccer-playing agents must possess the capability to learn and acquire low-level skills. These skills can later be put together and used to emulate the expertise of experienced players. This paper describes the use of reinforcement learning, a machine learning technique, to acquire the base level skills of intercepting a moving ball. Results of simulation runs using the Robocup Soccer server have also been presented.
Keywords :
digital simulation; games of skill; learning (artificial intelligence); mobile robots; multi-agent systems; multi-robot systems; RoboCup Soccer simulation; artificial intelligence; machine learning; multiagent system; reinforcement learning; soccer-playing agents; Artificial intelligence; Decision making; Game theory; Machine learning; Machine learning algorithms; Multiagent systems; Robots; Table lookup; Telematics; Testing;
Conference_Titel :
Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on
Print_ISBN :
0-7695-2291-2
DOI :
10.1109/ICHIS.2004.81