This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
We report on an investigation of the learning of coordination in cooperative multi-agent systems. Specifically, we study solutions that are applicable to independent agents i.e. ...
Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. ...
In this paper we partially describe JV2 M, a metaphorical simulation of the Java Virtual Machine where students can learn Java language compilation and reinforce object-oriented pr...
Abstract. The paper presents a method to guide the self-organised development of behaviours of autonomous robots. In earlier publications we demonstrated how to use the homeokinesi...
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...