Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327074 | Robotics and Autonomous Systems | 2005 | 13 Pages |
Abstract
In this paper, we investigate the feasibility of building action-planning mechanisms capable of autonomously determining task-achieving sequences of actions (plans), using previously acquired subsymbolic representations. These subsymbolic representations are acquired by the robot autonomously during an exploration phase. Furthermore, we investigate whether such subsymbolic mechanisms can employ generalisation techniques in order to pursue plans through unexplored regions of the robot's environment. Performance comparison of three subsymbolic action-planning mechanisms on different tasks conclude the paper.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
John Pisokas, Ulrich Nehmzow,