This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action ...
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...
We propose a mediator architecture that allows a learning system to retrieve learning objects from heterogeneous repositories. A mediating component accepts queries formulated in a...