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.
翻译:许多真实世界游戏包含影响报酬、行动空间和信息状态的参数。 对于参数的固定值, 游戏可以使用标准算法解决。 但是, 在许多设置中, 代理商必须操作时不知道事先会遇到的参数的值。 通常决定必须由人在时间和资源限制下做出, 假设一个人可以实时解决游戏是不现实的。 我们提出了一个新的框架, 使人类决策者能够在没有实时解算器帮助的情况下快速做出决定。 我们展示了对多种情况的适用性, 包括多玩家和不完善信息的设置。