Human strategic decision making in parametrized games
This addresses the challenge for humans in time-constrained real-world games, though it appears incremental as it builds on existing game-solving algorithms.
The paper tackles the problem of enabling human decision makers to make fast strategic decisions in parametrized games without real-time solvers, presenting a new framework that demonstrates applicability to various situations like multi-player and imperfect information settings.
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.