11:30 - 12:45 | Tue 30 May | Room 4611/4612 | TUB6
There has been a great deal of work on learning new robot skills, but very little consideration of how these newly acquired skills can be integrated into an overall intelligent system. A key aspect of such a system is compositionality: newly learned abilities have to be characterized in a form that will allow them to be flexibly combined with existing abilities, affording a (good!) combinatorial explosion in the robots abilities. In this paper, we focus on learning models of the preconditions and effects of new primitive actions, in a form that allows those actions to be combined with existing abilities by a generative planning and execution system.
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