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

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Document typeResearch report
Defense date2008
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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.
CitationAgostini, Alejandro; Wörgötter, Florentin; Celaya, Enric; Torras, Carme. "On-line learning of macro planning operators using probabilistic estimations of cause-effects". Technical Report IRI-DT-08-05, Institut de Robòtica i Informàtica Industrial, CSIC-UPC, 2008.