Introduction to the special issue on learning classifier systems

Special issue on advances in Learning Classifier Systems

Learning Classifier Systems (LCS) constitute a uniquely adaptable class of learning framework existing at the intersection of machine learning and evolutionary computation. Fundamentally, an LCS combines genetic search with an appropriate learning strategy to evolve a rule set which collectively describes a temporal or spatial problem. Since their conceptualization, a variety of algorithmic arc...

Introduction to the Special Issue on Learning Theory

This special issue builds on material presented at the Fifteens Annual Conference on Computational Learning Theory (COLT 2002) and the Sixteenth Annual Conference on Neural Information Processing Systems (NIPS*2002), held in Sydney in July 2002 and in Vancouver in December 2002, respectively. We contacted authors who presented work on the analysis of learning in general, and with a particular f...

Introduction to the special issue on probability, logic and learning

Editorial Introduction to the Special Issue on Learning Autonomous Robots

Programming an autonomous robot so that it reliably acts in a dynamic environment is a difficult thing to do. This is due to such problems as missing necessary information at design time, the unpredictability of the environment dynamics, and the inherent noise of the robot's sensors and actuators. For example, a robot may have to move in a cluttered environment with an a priori unknown topology...

Introduction to the special issue on discontinuity of fluvial systems

Available online 10 April 2013 Fluvial systems include natural and human-created barriers that modify local base level; as such, these discontinuities alter the longitudinal flux of water and sediment by storing, releasing, or changing the flow path of those materials. Even in the absence of distinct barriers, fluvial systems are typically discontinuous and patchy. The size of fluvial discontin...