Case - based reactive navigation : A case - based method for on - line selection and adaptation ofreactive control parameters in autonomous robotic systems Ashwin

This article presents a new line of research investigating on-line learning mechanisms for autonomous intelligent agents. We discuss a case-based method for dynamic selection and modiication of behavior assemblages for a navigational system. The case-based reasoning module is designed as an addition to a traditional reactive control system , and provides more exible performance in novel environments without extensive high-level reasoning that would otherwise slow the system down. The method is implemented in the ACBARR (A Case-BAsed Reactive Robotic) system, and evaluated through empirical simulation of the system on several diierent environments, including \box canyon" environments known to be problematic for reactive control systems in general.