Policy Learning with Hypothesis Based Local Action Selection

Sankaran, B.; Bohg, J.; Ratliff, N.; Schaal, S.

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Policy Learning with Hypothesis Based Local Action Selection

Sankaran, B., Bohg, J., Ratliff, N., & Schaal, S. (2015). Policy Learning with Hypothesis Based Local Action Selection. In Proceedings Reinforcement Learning and Decision Making (pp. 94-97). Arlington, VA: National Science Foundation.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-207D-9 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-5641-F

Genre: Conference Paper

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Creators:
Sankaran, B.¹, Author
Bohg, J.², Author
Ratliff, N.², Author
Schaal, S.², Author

Affiliations:
1External Organizations, ou_persistent22
2Dept. Autonomous Motion, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497646

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Free keywords: Abt. Schaal

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Dates: Published Online: 2015-06

Publication Status: Published online

Pages: 4

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Identifiers: BibTex Citekey: 1503

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Title: 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2015)

Place of Event: Edmonton, Alberta, Canada

Start-/End Date: 2015-06-07 - 2015-06-10

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Title: Proceedings Reinforcement Learning and Decision Making

Source Genre: Proceedings

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Publ. Info: Arlington, VA : National Science Foundation

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 94 - 97 Identifier: -