Reinforcement learning using potential field for role assignment in a multi-robot two-team game


Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics Engineering, Turkey

Approval Date: 2004

Student: FİDAN ÖZGÜL

Co-Supervisor: İSMET ERKMEN, AYDAN MÜŞERREF ERKMEN

Abstract:

In this work, reinforcement learning algorithms are studied with the help of potential field methods, using robosoccer simulators as test beds. Reinforcement Learning (RL) is a framework for general problem solving where an agent can learn through experience. The soccer game is selected as the problem domain a way of experimenting multi-agent team behaviors because of its popularity and complexity.