Learning RoboCup Skills
This project aims at applying Reinforcement Learning techniques for learning both low- and high-level skills for RoboCup robots.
Go To Ball Behavior
The Go To Ball is one of the simplest behaviors for a soccer robotic player. Although simple to implement by hand, it introduces many difficulties for the traditional RL algorithms. In particular, the continuous state and action space cannot be dealt with only through simple discretization because the learning process would be either too long or too unreliable (some details about the issues in learning in robotics applications can be found here). In this first experiment we tried to overcome these problems by using a novel RL algorithm: PWC-Q-learning (Piecewise Constant Q-learning).
- Alessandro Lazaric, PhD Student
- Marcello Restelli, PhD
- Moreno De Amicis, Master Student
A. Bonarini, A. Lazaric, M. Restelli - Piecewise Constant Reinforcement Learning for Robotic Applications
- 4th International Conference on Informatics in Control, Automation and Robotics (ICINCO) , 2007
- BibtexAuteur : A. Bonarini, A. Lazaric, M. Restelli
Titre : Piecewise Constant Reinforcement Learning for Robotic Applications
Dans : 4th International Conference on Informatics in Control, Automation and Robotics (ICINCO) -
Date : 2007