arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2104.14744cs.GTcs.AIcs.LGecon.TH
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参数化游戏中的人类战略决策

Human strategic decision making in parametrized games

Ganzfried Research(甘兹弗里德研究)

Sam Ganzfried

AI总结:

本文提出一种框架,使人类能在无需实时求解器的情况下快速做出决策,适用于多玩家和不完全信息环境。

摘要:

许多现实世界的游戏包含参数,这些参数会影响支付、行动空间和信息状态。对于固定参数值,游戏可以使用标准算法求解。然而,在许多情况下,代理必须在不知晓将要遇到的参数值的情况下行动。通常,决策必须由人类在时间和资源限制下做出,无法假设人类能实时求解游戏。本文提出了一种新框架,使人类决策者能够在不借助实时求解器的情况下快速做出决策,并展示了其在多种情况中的适用性,包括多玩家和不完全信息环境。

英文摘要:

Many real-world games contain parameters which can affect payoffs, action spaces, and information states. For fixed values of the parameters, the game can be solved using standard algorithms. However, in many settings agents must act without knowing the values of the parameters that will be encountered in advance. Often the decisions must be made by a human under time and resource constraints, and it is unrealistic to assume that a human can solve the game in real time. We present a new framework that enables human decision makers to make fast decisions without the aid of real-time solvers. We demonstrate applicability to a variety of situations including settings with multiple players and imperfect information.

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。

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