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AlphaDDA: strategies for adjusting the playing strength of a fully trained AlphaZero system to a suitable human training partner
Author(s) -
Kazuhisa Fujita
Publication year - 2022
Publication title -
peerj computer science
Language(s) - English
Resource type - Journals
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.1123
Subject(s) - monte carlo tree search , computer science , artificial intelligence , context (archaeology) , minimax , value (mathematics) , game tree , artificial neural network , state (computer science) , adversary , monte carlo method , machine learning , sequential game , game theory , mathematical optimization , algorithm , mathematical economics , mathematics , statistics , computer security , paleontology , biology

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