Learning and Game AI

Hector Muñoz-Avila, C. Bauckhage, M. Bída, C. Congdon, G. Kendall
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引用次数: 16

Abstract

The incorporation of learning into commercial games can enrich the player experience, but may concern developers in terms of issues such as losing control of their game world. We explore a number of applied research and some fielded applications that point to the tremendous possibilities of machine learning research including game genres such as real-time strategy games, flight simulation games, car and motorcycle racing games, board games such as Go, an even traditional game-theoretic problems such as the prisoners dilemma. A common trait of these works is the potential of machine learning to reduce the burden of game developers. However a number of challenges exists that hinder the use of machine learning more broadly. We discuss some of these challenges while at the same time exploring opportunities for a wide use of machine learning in games.
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学习和游戏AI
将学习融入商业游戏可以丰富玩家体验,但可能会让开发者担心失去对游戏世界的控制等问题。我们探索了一些应用研究和一些领域的应用,这些应用指出了机器学习研究的巨大可能性,包括游戏类型,如实时战略游戏,飞行模拟游戏,汽车和摩托车赛车游戏,棋盘游戏,如围棋,甚至是传统的博弈论问题,如囚犯困境。这些作品的一个共同特点是机器学习可以减轻游戏开发者的负担。然而,存在一些阻碍机器学习更广泛使用的挑战。我们讨论了其中的一些挑战,同时探索了在游戏中广泛使用机器学习的机会。
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