General Video Game Playing
General Video Game Playing
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一般视频游戏
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Tommy Thompson
中科院分区：
文献类型：
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作者：
J. Levine;C. Congdon;M. Ebner;G. Kendall;S. Lucas;R. Miikkulainen;T. Schaul;Tommy Thompson
AI的巨大挑战之一是创建一般情报：可以在许多任务上脱颖而出的代理，而不仅仅是一项任务。在游戏领域，这引起了一般游戏（GGP）的挑战。在GGP中，游戏（通常是转弯棋盘游戏）是根据游戏的逻辑来宣告定义的（何时进行移动，评分系统的工作方式，如何宣布获胜者，等等） 。然后，AI播放器必须弄清楚如何玩游戏以及如何获胜。在这项工作中，我们试图将一般游戏玩法的想法扩展到视频游戏领域，从而形成一般视频游戏的领域（GVGP）。在GVGP中，将要求计算代理玩他们以前从未见过的视频游戏。至少，将给予代理人的当前状态，并告诉适用哪些行动。每个游戏都必须决定其行动，并考虑到游戏和游戏物理学中其他代理商的动作，并将更新状态。我们设想使用Arcadestyle（例如，与Atari 2600）游戏作为我们的起点进行基于GVGP演奏的比赛。这些游戏足够丰富，可以成为GVGP代理商的巨大挑战，而没有引入不必要的复杂性。我们设想的竞争可以基于状态的形式（帧缓冲区或对象模型）以及是否可用的动作执行模型具有许多曲目。我们建议可以为我们的目的扩展现有的物理旅行推销员（PTSP）软件，并且可以由AI，游戏学生和其他开发人员在此框架中创建各种GVGP游戏。除此之外，我们设想开发视频游戏说明语言（VGDL），以简洁地指定视频游戏。在竞争中，我们认为这是一个有趣的挑战，在审查，机器学习以及将现有知识转移到新领域方面。
One of the grand challenges of AI is to create general intelligence: an agent that can excel at many tasks, not just one. In the area of games, this has given rise to the challenge of General Game Playing (GGP). In GGP, the game (typically a turn-taking board game) is defined declaratively in terms of the logic of the game (what happens when a move is made, how the scoring system works, how the winner is declared, and so on). The AI player then has to work out how to play the game and how to win. In this work, we seek to extend the idea of General Game Playing into the realm of video games, thus forming the area of General Video Game Playing (GVGP). In GVGP, computational agents will be asked to play video games that they have not seen before. At the minimum, the agent will be given the current state of the world and told what actions are applicable. Every game tick the agent will have to decide on its action, and the state will be updated, taking into account the actions of the other agents in the game and the game physics. We envisage running a competition based on GVGP playing, using arcadestyle (e.g. similar to Atari 2600) games as our starting point. These games are rich enough to be a formidable challenge to a GVGP agent, without introducing unnecessary complexity. The competition that we envisage could have a number of tracks, based on the form of the state (frame buffer or object model) and whether or not a forward model of action execution is available. We propose that the existing Physical Travelling Salesman (PTSP) software could be extended for our purposes and that a variety of GVGP games could be created in this framework by AI and Games students and other developers. Beyond this, we envisage the development of a Video Game Description Language (VGDL) as a way of concisely specifying video games. For the competition, we see this as being an interesting challenge in terms of deliberative search, machine learning and transfer of existing knowledge into new domains.