Vision-Based Reinforcement Learning for RoboCup: Towards Real Robot Competition
Eiji Uchibe, Minoru Asada, Shoichi Noda, Yasutake Takahashi, Koh Hosoda · 1996
We have been doing a research on vision-based reinforcement learning and applied the method to build real soccer playing robots towards RoboCup Initiative. In the rst stage [4, 2], a robot learned to shoot a ball into a goal given the state space in terms of the sizes and the positions of both the ball and the goal in image. In the second stage [4], we set up an opponent just before the goal, that is, a goal keeper, and make the robot learn to shoot a ball into a goal avoiding the goal keeper. The behavior of the opponent is scheduled for the learner to eciently obtain the desired behavior [3]. This paper describes several research issues for RoboCup with real robots along with our research projects. 1 Introduction Building robots that learn to perform a task has been acknowledged as one of the major challenges facing AI and Robotics. Reinforcement learning has recently been receiving increased attention as a method for robot learning with little or no a priori knowledge and higher...