Potential Energy and Particle Interaction Approach for Learning in Adaptive Systems [chapter]

Deniz Erdogmus, Jose C. Principe, Luis Vielva, David Luengo
2002 Lecture Notes in Computer Science  
Adaptive systems research is mainly concentrated around optimizing cost functions suitable to problems. Recently, Principe et al. proposed a particle interaction model for information theoretical learning. In this paper, inspired by this idea, we propose a generalization to the particle interaction model for learning and system adaptation. In addition, for the special case of supervised multi-layer perceptron (MLP) training we propose the interaction force backpropagation algorithm, which is a
more » ... eneralization of the standard error backpropagation algorithm for MLPs.
doi:10.1007/3-540-46084-5_74 fatcat:4drnippj55bgncfuoizjs2w3hm