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Improving Hearthstone AI by Combining MCTS and Supervised Learning
  Algorithms

Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms

14 August 2018
M. Świechowski
T. Tajmajer
Andrzej Janusz
    BDL
ArXivPDFHTML

Papers citing "Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms"

4 / 4 papers shown
Title
Optimizing Hearthstone Agents using an Evolutionary Algorithm
Optimizing Hearthstone Agents using an Evolutionary Algorithm
Pablo García-Sánchez
Alberto Tonda
Antonio J. Fernández-Leiva
Carlos Cotta
55
24
0
25 Oct 2024
MCTS Based Agents for Multistage Single-Player Card Game
MCTS Based Agents for Multistage Single-Player Card Game
Konrad Godlewski
B. Sawicki
11
2
0
24 Sep 2021
Monte Carlo Tree Search: A Review of Recent Modifications and
  Applications
Monte Carlo Tree Search: A Review of Recent Modifications and Applications
M. Świechowski
Konrad Godlewski
B. Sawicki
Jacek Mańdziuk
41
249
0
08 Mar 2021
Covariance Matrix Adaptation for the Rapid Illumination of Behavior
  Space
Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space
Matthew C. Fontaine
Julian Togelius
Stefanos Nikolaidis
Amy K. Hoover
48
134
0
05 Dec 2019
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