In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Abstract. Classical conditioning is a basic learning mechanism in animals and can be found in almost all organisms. If we want to construct robots with abilities matching those of ...
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...