经验博弈论分析与软件代理行为Empirical Game-Theoretic Analysis and the Behavior of Software Agents |
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课程网址: | http://videolectures.net/icaps2011_wellman_game/ |
主讲教师: | Wellman Michael P |
开课单位: | 密西根大学 |
开课时间: | 2011-07-21 |
课程语种: | 英语 |
中文简介: | 在市场、冲突或大多数其他情况下,游戏代理通常会无视严格的游戏理论分析。游戏可能是不可管理的大(组合的或无限的状态或动作空间),并且存在严重的不完全信息,这可能会因部分动态揭示而进一步复杂化。此外,游戏可以通过程序指定,例如由模拟器指定,而不是以明确的游戏形式指定。在过去的几年中,我与同事和学生一起开发了一系列战略分析技术,采用了博弈论框架,但将其应用于直接建模和求解不适用的领域。这种经验博弈论方法包括模拟、近似、统计和学习以及搜索。通过对典型拍卖游戏的应用,以及丰富的交易场景,论证了经验方法在扩大博弈理论分析范围方面的价值。这一观点也揭示了对复杂多智能体场景中预测联合行动的行为模型和基础的洞察。 |
课程简介: | The games agents play - in markets, conflicts, or most other contexts - often defy strict game-theoretic analysis. Games may be unmanageably large (combinatorial or infinite state or action spaces), and present severely imperfect information, which could be further complicated by partial dynamic revelation. Moreover, the game may be specified procedurally, for instance by a simulator, rather than in an explicit game form. With colleagues and students over the past few years, I have been developing a body of techniques for strategic analysis, adopting the game-theoretic framework but employing it in domains where direct "model-and-solve" cannot apply. This empirical game-theoretic methodology embraces simulation, approximation, statistics and learning, and search. Through applications to canonical auction games, and rich trading scenarios, we demonstrate the value of empirical methods for extending the scope of game-theoretic analysis. This perspective also sheds insight into behavioral models and bases for predicting joint action in complex multiagent scenarios. |
关 键 词: | 游戏代理商; 博弈论; 多智能体 |
课程来源: | 视频讲座网 |
最后编审: | 2020-09-28:heyf |
阅读次数: | 84 |