Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
This paper presents an efficient method of learning motion control for autonomous animated characters. The method uses a non parametric learning approach which identifies non line...
Engineering individual components of a multi-agent system and their interactions is a complex and error-prone task in urgent need of methods and tools. Prototyping is a valuable t...
Wamberto Weber Vasconcelos, Carles Sierra, Marc Es...
In RoboCup-98, sparrows team worked hard just to get both a simulation and a middle size robot team to work and to successfully participate in a major tournament. For this year, we...