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川普在美国宾州巴特勒的一次演讲中遇刺_20240714川普在美国宾州巴特勒的一次演讲中遇刺_20240714
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根据您提供的信息,以下是关于清华大学、北京大学等机构发布的Self-Play强化学习最新综述的概要信息,适合作为新闻报道或编辑摘要使用:


标题:清华、北大等联合发布Self-Play强化学习最新综述:推动AI算法研究新进展

正文:

近日,清华大学电子工程系、北京大学人工智能研究院、第四范式、腾讯及清华-伯克利深圳学院等机构联合发布了一篇关于Self-Play强化学习的最新综述。该综述由清华大学硕士张瑞泽担任第一作者,通讯作者为清华大学电子工程系汪玉教授、于超博后和第四范式研究员黄世宇博士。

Self-Play,即自博弈,是一种智能体通过与自身副本或历史版本进行博弈而进行演化的方法,近年来在强化学习领域受到广泛关注。这篇综述详细梳理了自博弈的基本背景,包括多智能体强化学习框架和博弈论的基础知识。

文章提出了一个统一的自博弈算法框架,并在此基础上对现有的自博弈算法进行了分类和对比,包括传统自博弈算法、PSRO系列算法、基于持续训练的系列算法和后悔最小化系列算法。此外,综述还通过展示自博弈在不同场景下的应用,架起了理论与实践之间的桥梁。

该综述最后总结了自博弈面临的开放性挑战,并对未来研究方向进行了探讨。论文题目为《A Survey on Self-play Methods in Reinforcement Learning》,已发布在AIxiv专栏,该专栏由机器之心运营,致力于发布学术、技术内容,促进学术交流与传播。

对于有兴趣深入了解自博弈强化学习的研究人员和学生,可通过以下论文链接获取更多信息:https://arxiv.org/abs/2408.01072


请注意,以上内容是基于您提供的信息编写的,具体的论文内容和细节可能需要进一步查阅原文以获取准确信息。


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