Human strategic decision making in parametrized games

TL;DR

This paper introduces a framework that helps humans make quick strategic decisions in complex, parametrized games where traditional algorithms are impractical due to unknown parameters and real-time constraints.

Contribution

The authors propose a novel approach enabling humans to efficiently decide in parametrized games without relying on real-time computational solvers.

Findings

Framework applicable to multi-player games

Effective under imperfect information

Supports rapid decision making for humans

Abstract

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.