On-line Inference of Off-line Learned Operational Concepts Export

@misc{citeulike:1186429, abstract = {. Learning in robotics has received more and more attention in recent years. It eases bridging the gap between low-level sensor data and high-level concepts. A high-level representation language is necessary in order to support the communication between robot and user in both directions when the robot navigates in unknown environments. Controlling robots in terms of a high-level representation formalism like first-order logic is often said to be too slow. In this paper, we present a performance ...}, author = {Klingspor, Volker}, citeulike-article-id = {1186429}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8842}, keywords = {robotics}, posted-at = {2007-03-26 03:08:16}, priority = {2}, title = {On-line Inference of Off-line Learned Operational Concepts}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8842} }

TY - GEN ID - citeulike:1186429 L3 - citeulike-article-id:1186429 N2 - . Learning in robotics has received more and more attention in recent years. It eases bridging the gap between low-level sensor data and high-level concepts. A high-level representation language is necessary in order to support the communication between robot and user in both directions when the robot navigates in unknown environments. Controlling robots in terms of a high-level representation formalism like first-order logic is often said to be too slow. In this paper, we present a performance ... TI - On-line Inference of Off-line Learned Operational Concepts KW - robotics AU - Klingspor, Volker UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.8842 ER -