Author Description

An August 2008 symposium brought together researchers from academia and industry to report on new concepts, laboratory demonstrations, and fielded robotic systems that exhibit learning and adaptive behaviors. The goal of the symposium was to map future directions for the development of robotic systems with capabilities comparable to those of biological systems. Papers from the symposium are collected here. Some specific areas examined include mixture model segmentation for gait recognition, evolvability of neuromodulated learning for robots, learning vision algorithms for real mobile robots with generic programming, surprise-based learning for developmental robotics, and a dual robust controller design for a high-power AC servo drive. There is no subject index.