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  Admissible Policy Teaching through Reward Design

Banihashem, K., Singla, A., Gan, J., & Radanovic, G. (2022). Admissible Policy Teaching through Reward Design. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (pp. 6037-6045). Palo Alto, CA: AAAI. doi:10.1609/aaai.v36i6.20550.

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Genre: Conference Paper

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 Creators:
Banihashem, Kiarash1, Author           
Singla, Adish1, Author                 
Gan, Jiarui2, Author           
Radanovic, Goran3, Author           
Affiliations:
1Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society, ou_2541698              
2Group R. Majumdar, Max Planck Institute for Software Systems, Max Planck Society, ou_2105292              
3Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Banihashem_AAAI22
DOI: 10.1609/aaai.v36i6.20550
 Degree: -

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Title: 36th AAAI Conference on Artificial Intelligence
Place of Event: Virtual Conference
Start-/End Date: 2022-02-22 - 2022-03-01

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Project name : HumanML
Grant ID : 945719
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Proceedings of the 36th AAAI Conference on Artificial Intelligence
  Abbreviation : AAAI 2022
  Subtitle : AAAI-22 Technical Tracks 6
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Palo Alto, CA : AAAI
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 6037 - 6045 Identifier: ISBN: 978-1-57735-876-3