Learning reliable manipulation strategies without initial physical modelsA description is given of a robot, possessing limited sensory and effectory capabilities but no initial model of the effects of its actions on the world, that acquires such a model through exploration, practice, and observation. By acquiring an increasingly correct model of its actions, it generates increasingly successful plans to achieve its goals. In an apparently nondeterministic world, achieving reliability requires the identification of reliable actions and a preference for using such actions. Furthermore, by selecting its training actions carefully, the robot can significantly improve its learning rate.
Document ID
19910050565
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Christiansen, Alan D. (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Mason, Matthew T. (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Mitchell, Tom M. (Carnegie Mellon University Pittsburgh, PA, United States)