The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
—It is desirable that colony robots be autonomous and self-sufficient, which requires that they can perform their duties while maintaining enough energy to operate. In previous w...
We review a neuroplanner architecture for use in constructing subcognitive controllers and new application that uses it. These controllers have wo important properties: (1) the ab...
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...