Do people think like computers?

Abstract

Human cognition inspired the earliest algorithms for game playing computer programs. However, the studies of human and computer game play quickly diverged: the Artificial Intelligence community focused on theory and techniques to solve games, while behavioral scientists empirically examined simple decision-making in humans. In this paper, we combine concepts and methods from the two fields to investigate whether human and AI players take similar approaches in an adversarial combinatorial game. We develop and compare five models that capture human behavior. We then demonstrate that our models can predict behavior in two related tasks. To conclude, we use our models to describe what makes a strong human player.