Information in the nervous system has often been considered as being represented by simultaneous discharge of a large set of neurons. We propose a learning mechanism for neural inf...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
In this paper, biological (human) music composition systems based on Time Delay Neural Networks and Ward Nets and on a probabilistic Finite-State Machine will be presented. The sys...
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...