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Criado por administrar Última atualização em 12/12/2018 - 18:00
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Writing artificial intelligence (AI) might be the best job in games. It’s creative, challenging, and blurs the line between game design and programming. AI is used for a variety of tasks ranging from the mechanical (such as auto-attacking enemies) and bot AI, to flocking group intelligence, even to deep-thinking military generals. Games that emphasize story and character-based immersion such as...
Criado por Coppock, Michael J (Intel) Última atualização em 30/05/2018 - 07:00
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为《Lords of New York》* 构建以个性为驱动的扑克牌 AI

Writing artificial intelligence (AI) might be the best job in games. It’s creative, challenging, and blurs the line between game design and programming. AI is used for a variety of tasks ranging from the mechanical (such as auto-attacking enemies) and bot AI, to flocking group intelligence, even to deep-thinking military generals. Games that emphasize story and character-based immersion such as...
Criado por Coppock, Michael J (Intel) Última atualização em 30/05/2018 - 07:00
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Criado por Carman, Vicky (Intel) Última atualização em 03/07/2019 - 19:10
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This article will show game developers how to use reinforcement learning to create better artificial intelligence (AI) behavior. Using Intel® Distribution for Python—an improved version of the popular object-oriented, high-level programming language—readers will glean how to train pre-existing machine-language (ML) agents to learn and adapt. In this scenario, we will use Intel® Optimization for...
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本文将向游戏开发人员介绍如何使用强化学习创建更好的人工智能 (AI) 行为。使用 Python* 的英特尔® 分发版 — 常用面向对象的高级编程语言的进阶版 — 读者可收集关于如何训练预先存在的机器语言 (ML) 代理学习和适应的信息。在此场景下,我们将使用英特尔® Optimization for TensorFlow* 在本地化环境中运行 Unity * ML-Agents。
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