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Explanation-based manipulator learning: Acquisition of planning ability through observation

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2 Author(s)
Segre, A. ; University of Illinois at Urbana-Champaign Urbana, IL ; DeJong, Gerald

This paper describes a robot manipulator system currently under development which learns from observation. The system improves its problem-solving capabilities through the acquisition of task-related concepts. The system observes manipulator command sequences that solve problems currently beyond its own panning abilities. General problem-solving schemata are automatically constructed via a knowledge-based analysis of how the observed command sequence achieved the goal. This learning technique is based on explanatory schema acquisition. It is a knowledge-based approach, requiring sufficient background knowledge to understand the observed sequence. The acquired schemata serve two purposes: they allow the system to solve problems that were previously unsolvable, and they aid in the understanding of later observations.

Published in:

Robotics and Automation. Proceedings. 1985 IEEE International Conference on  (Volume:2 )

Date of Conference:

Mar 1985

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