Modeling Single-Task Performance Improvement Using EPIC-Soar

Ninth Midwest Artificial intelligence and Cognitive Science Conference

Volume

Ninth Midwest Artificial intelligence and Cognitive Science Conference

Contents

We present a task-independent learning procedure which produces gradual performance improvement through experience on a perceptual-motor task. It utilizes a data structure that represents a strategy for performing the task. This learning procedure is a direct result of the constraints that occur when realistic perceptual and motor mechanisms (EPIC) are mated to a learning cognitive modeling architecture (Soar).