Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding

7 December 2021

Papers citing "Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding"

8 / 8 papers shown

Title
Measuring Diversity of Game Scenarios Yuchen Li Ziqi Wang Qingquan Zhang Jialin Liu J. Liu 61 2 0 17 Jan 2025
Optimizing Hearthstone Agents using an Evolutionary Algorithm Pablo García-Sánchez Alberto Tonda Antonio J. Fernández-Leiva Carlos Cotta 48 24 0 25 Oct 2024
Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables Loïc Brevault M. Balesdent 25 2 0 11 Sep 2023
Fitness Approximation through Machine Learning Itai Tzruia Tomer Halperin Moshe Sipper Achiya Elyasaf 8 2 0 06 Sep 2023
Efficient Quality-Diversity Optimization through Diverse Quality Species Ryan Wickman Bibek Poudel Taylor Michael Villarreal Xiaofei Zhang Weizi Li 10 6 0 14 Apr 2023
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires Bryan Lim Luca Grillotti Lorenzo Bernasconi Antoine Cully 57 28 0 16 Sep 2021
Quality-Diversity Optimization: a novel branch of stochastic optimization Konstantinos Chatzilygeroudis Antoine Cully Vassilis Vassiliades Jean-Baptiste Mouret 58 91 0 08 Dec 2020
Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms M. Świechowski T. Tajmajer Andrzej Janusz BDL 45 59 0 14 Aug 2018