Subjective Mapping

Michael H. Bowling, Dana F. Wilkinson, Ali Ghodsi

Abstract: Subjective Mapping Michael Bowling, Dana Wilkinson, Ali Ghodsi Extracting a map from a stream of experience is a key problem in robotics and artificial intelligence in general. We propose a technique, called subjective mapping, that seeks to learn a fully specified predictive model, or map, without the need for expert provided models of the robot's motion and sensor apparatus. We briefly overview the recent advancements presented elsewhere (ICML, IJCAI, and ISRR) that make this possible, examine its significance in relationship to other developments in the field, and outline open issues that remain to be addressed. Subjects: 12. Machine Learning and Discovery; 17. Robotics This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.