Parameterized MDPs and Reinforcement Learning Problems—A Maximum Entropy Principle-Based Framework

Srivastava, Amber; Salapaka, Srinivasa M.

doi:10.1109/tcyb.2021.3102510

Parameterized MDPs and Reinforcement Learning Problems—A Maximum Entropy Principle-Based Framework

Journal Article · 01 September 2022 · IEEE Transactions on Cybernetics

DOI:https://doi.org/10.1109/tcyb.2021.3102510· OSTI ID:1980477

^[1]; ^[2]

Mechanical Science and Engineering Department and Coordinated Science Laboratory, University of Illinois at Urbana–,Champaign, Urbana, IL, USA; OSTI
Mechanical Science and Engineering Department and Coordinated Science Laboratory, University of Illinois at Urbana–,Champaign, Urbana, IL, USA

Not provided.

Research Organization:: Worcester Polytechnic Institute, MA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

DOE Contract Number:: EE0009125;

OSTI ID:: 1980477

Journal Information:: IEEE Transactions on Cybernetics, Journal Name: IEEE Transactions on Cybernetics Journal Issue: 9 Vol. 52; ISSN 2168-2267

Publisher:: IEEE

Country of Publication:: United States

Language:: English

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