AlphaStar：一个演化计算的视角
AlphaStar: An Evolutionary Computation Perspective
摘要：
2019年1月，DeepMind向全世界展示了AlphaStar--第一个在《星际争霸2》游戏中击败职业玩家的人工智能（AI）系统--代表了AI进步的里程碑。AlphaStar借鉴了人工智能研究的许多领域，包括深度学习、强化学习、博弈论和演化计算（EC）。在本文中，我们主要通过EC的镜头来分析AlphaStar，对该系统进行了新的审视，并将其与该领域的许多概念联系起来。我们强调了一些最有趣的方面-拉马克进化，竞争性共同进化和质量多样性的使用。通过这样做，我们希望在更广泛的电子商务社区和近年来开发的最重要的人工智能系统之一之间架起一座桥梁。
英文摘要：
In January 2019, DeepMind revealed AlphaStar to the world-the first artificial intelligence (AI) system to beat a professional player at the game of StarCraft II-representing a milestone in the progress of AI. AlphaStar draws on many areas of AI research, including deep learning, reinforcement learning, game theory, and evolutionary computation (EC). In this paper we analyze AlphaStar primarily through the lens of EC, presenting a new look at the system and relating it to many concepts in the field. We highlight some of its most interesting aspects-the use of Lamarckian evolution, competitive co-evolution, and quality diversity. In doing so, we hope to provide a bridge between the wider EC community and one of the most significant AI systems developed in recent times.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
