Search Results for author:
Found 3 papers, 2 papers with code
Evolutionary Tabletop Game Design: A Case Study in the Risk Game
Evolutionary game design, which combines evolutionary algorithms with automated playtesting, has been used to create novel board games with simple equipment; however, the original approach does not include complex tabletop games with dice, cards, and maps.
Hybrid Minimax-MCTS and Difficulty Adjustment for General Game Playing
In this paper, we present a general approach to implement an artificial intelligence opponent with difficulty levels for zero-sum games, together with a propose of a Minimax-MCTS hybrid algorithm, which combines the minimax search process with GGP aspects of MCTS.
Drafting in Collectible Card Games via Reinforcement Learning
In this paper, we present a deep reinforcement learning approach for deck building in arena mode - an understudied game mode present in many collectible card games.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
