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Learning Symbolic Representations for Planning with Parameterized Skills

Publication ,  Conference
Ames, B; Thackston, A; Konidaris, G
Published in: IEEE International Conference on Intelligent Robots and Systems
December 27, 2018

A critical capability required for generally intelligent robot behavior is the ability to sequence motor skills to reach a goal. This requires a (typically abstract) representation that supports goal-directed planning, which raises the question of how to construct such a representation. Previous work has addressed this question in the context of simple black-box motor skills, which are insufficiently flexible to support the wide range of behavior required of intelligent robots. We now extend that work to include parametrized motor skills, where a robot must both select an action to execute and also decide how to parametrize it. We show how to construct a representation suitable for planning with parametrized motor skills, and specify conditions which are sufficient to separate the selection of motor skills from the parametrization of those skills. Our method results in a simple discrete abstract representation for planning followed by a parameter selection process that operates on a fixed plan. We first demonstrate learning this representation in a virtual domain based on Angry Birds and then learn an abstract symbolic representation for a robot manipulation task.

Duke Scholars

Published In

IEEE International Conference on Intelligent Robots and Systems

DOI

EISSN

2153-0866

ISSN

2153-0858

ISBN

9781538680940

Publication Date

December 27, 2018

Start / End Page

526 / 533
 

Citation

APA
Chicago
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MLA
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Ames, B., Thackston, A., & Konidaris, G. (2018). Learning Symbolic Representations for Planning with Parameterized Skills. In IEEE International Conference on Intelligent Robots and Systems (pp. 526–533). https://doi.org/10.1109/IROS.2018.8594313
Ames, B., A. Thackston, and G. Konidaris. “Learning Symbolic Representations for Planning with Parameterized Skills.” In IEEE International Conference on Intelligent Robots and Systems, 526–33, 2018. https://doi.org/10.1109/IROS.2018.8594313.
Ames B, Thackston A, Konidaris G. Learning Symbolic Representations for Planning with Parameterized Skills. In: IEEE International Conference on Intelligent Robots and Systems. 2018. p. 526–33.
Ames, B., et al. “Learning Symbolic Representations for Planning with Parameterized Skills.” IEEE International Conference on Intelligent Robots and Systems, 2018, pp. 526–33. Scopus, doi:10.1109/IROS.2018.8594313.
Ames B, Thackston A, Konidaris G. Learning Symbolic Representations for Planning with Parameterized Skills. IEEE International Conference on Intelligent Robots and Systems. 2018. p. 526–533.

Published In

IEEE International Conference on Intelligent Robots and Systems

DOI

EISSN

2153-0866

ISSN

2153-0858

ISBN

9781538680940

Publication Date

December 27, 2018

Start / End Page

526 / 533