Recently, a Competitive Exception Learning Algorithm (CELA) was introduced [1, 2]. This algorithm establishes an optimal mapping from a (continuous) M-dimensional input sample space to an N-dimensional (continuous) output sample space. CELA is aimed to discover regimes (i.e. local behavior in...

A number of experimental studies have investigated whether cooperative behavior may emerge in multi-agent Q-learning. In some studies cooperative behavior did emerge, in others it did not. This report provides a theoretical analysis of this issue. The analysis focuses on multi-agent Q-learning...

A competitive exception learning algorithm for finding a non-linear mapping is proposed which puts the emphasis on the discovery of the important exceptions rather than the main rules. To do so,we first cluster the output space using a competitive fuzzy clustering algorithm and derive a fuzzy...