We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
While most theoretical work in machine learning has focused on the complexity of learning, recently there has been increasing interest in formally studying the complexity of teach...
This paper introduces a foundation for inductive learning based on the use of higher-order logic for knowledge representation. In particular, the paper (i) provides a systematic i...
Antony F. Bowers, Christophe G. Giraud-Carrier, Jo...
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...