ゲームAI
Minecraft のエージェントAI
Minecraft® はプレイヤーが 3D サンドボックスの世界を探索するゲームです。Minecraft® のゲームAIは、プレイヤーと同じようにリソースを集め、探索をし、何かの目的を達成することになります。 例えば、ダイヤモンドを採るために素材を集め、道具を作るように学習をさせます。良いナビゲーションと、適切な方策の設定が重要です。
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Computing Equilibrium Strategies for Collectible Card Game with Counterfactual Regret Minimization
Deck creation and game play of a collectible card game Hearthstone by using Counterfactual Regret Minimization (CFR), which is a family of mature algorithms and currently the most efficient method for computing Nash equilibria in large, zero-sum, imperfect information game. As Hearthstone has more than one actions in one round such as attack, play cards, cast spells or pass and has a few kinds of cards such as summon miniones, spells that affect the battle field are then discarded or weapons which give heroes strength to attack, we considered action sequences as a tie of states node in the game tree.Furthermore, CFR would compute regret for each action that player executed and including choosing a card from the card pool to construct a deck.
内部報酬を利用したローグライクゲームの強化学習
内部報酬を利用して、ローグライクゲームを解くようなゲームAIの強化学習を行います。