Publication

On-line learning of macro planning operators using probabilistic estimations of cause-effects

Technical Report (2008)

IRI code

IRI-TR-08-05

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Abstract

In this work we propose an on-line learning method for learning action rules for planning. The system uses a probabilistic approach of a constructive induction method that combines a beam search with an example-based search over candidate rules to find those that more concisely describe the world dynamics. The approach permits a rapid integration of the knowledge acquired from experience. Exploration of the world dynamics is guided by the planner, and – if the planner fails because of incomplete knowledge – by a teacher through action instructions.

Categories

intelligent robots, learning (artificial intelligence), planning (artificial intelligence), service robots.

Author keywords

online learning, macro planning operator, constructive learning

Scientific reference

A. Agostini, F. Wörgötter, E. Celaya and C. Torras. On-line learning of macro planning operators using probabilistic estimations of cause-effects. Technical Report IRI-TR-08-05, Institut de Robòtica i Informàtica Industrial, CSIC-UPC, 2008.