“第三十二章 AI游戏”版本间的差异
来自cslt Wiki
（以“==教学资料== * 教学参考 * [http://aigraph.cslt.org/courses/32/course-32.pptx 课件] * 小清爱提问：阿尔法狗和深蓝算法有...”为内容创建页面） |
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* [[教学参考-32|教学参考]] | * [[教学参考-32|教学参考]] | ||
* [http://aigraph.cslt.org/courses/32/course-32.pptx 课件] | * [http://aigraph.cslt.org/courses/32/course-32.pptx 课件] | ||
| − | * | + | * 小清爱提问：机器如何学会打游戏？ ？ [https://mp.weixin.qq.com/s?__biz=Mzk0NjIzMzI2MQ==&mid=2247485815&idx=1&sn=e7f80182a71b1820fd52266faef4f45e&chksm=c30803b5f47f8aa3ae32e138b67447318fd64c1b42837447073e58de7241cd348da5aa136a17&scene=178#rd] |
==扩展阅读== | ==扩展阅读== | ||
| − | + | *AI 100问：机器如何学会打游戏？ [[http://aigraph.cslt.org/ai100/AI-100-82-机器如何学会打游戏.pdf] | |
| + | * OpenAI 捉迷藏游戏[https://openai.com/blog/emergent-tool-use/] | ||
| + | * DeepMind AlphaStar 博客 [https://www.deepmind.com/blog/alphastar-mastering-the-real-time-strategy-game-starcraft-ii] | ||
==视频展示== | ==视频展示== | ||
| + | * OpenAI Hide and Seek [http://aigraph.cslt.org/courses/32/Multi-Agent.mp4] | ||
==演示链接== | ==演示链接== | ||
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* Mnih V, Kavukcuoglu K, Silver D, et al. Human-level control through deep reinforcement learning[J]. nature, 2015, 518(7540): 529-533. [https://daiwk.github.io/assets/dqn.pdf] | * Mnih V, Kavukcuoglu K, Silver D, et al. Human-level control through deep reinforcement learning[J]. nature, 2015, 518(7540): 529-533. [https://daiwk.github.io/assets/dqn.pdf] | ||
| − | * | + | * Baker B, Kanitscheider I, Markov T, et al. Emergent tool use from multi-agent autocurricula[J]. arXiv preprint arXiv:1909.07528, 2019. [https://arxiv.org/pdf/1909.07528] |
| + | * Arulkumaran K, Cully A, Togelius J. Alphastar: An evolutionary computation perspective[C]//Proceedings of the genetic and evolutionary computation conference companion. 2019: 314-315. [https://arxiv.org/pdf/1902.01724] | ||
2022年8月13日 (六) 08:29的版本
教学资料
扩展阅读
视频展示
- OpenAI Hide and Seek [5]
演示链接
开发者资源
高级读者
- Mnih V, Kavukcuoglu K, Silver D, et al. Human-level control through deep reinforcement learning[J]. nature, 2015, 518(7540): 529-533. [6]
- Baker B, Kanitscheider I, Markov T, et al. Emergent tool use from multi-agent autocurricula[J]. arXiv preprint arXiv:1909.07528, 2019. [7]
- Arulkumaran K, Cully A, Togelius J. Alphastar: An evolutionary computation perspective[C]//Proceedings of the genetic and evolutionary computation conference companion. 2019: 314-315. [8]
