Understanding stochastic decision-making in competitive multi-agent environments
Stochastic strategies are often advantageous in competitive environments to prevent opponents from predicting one’s actions. To study how stochastic behaviours arise, we trained head-fixed mice to play a zero-sum game, Matching Pennies, in which the optimal behaviour against a rational agent is to choose between actions with equal probability. On each trial, mice chose between two available actions: lick left or right. A computer opponent predicted each animal’s upcoming choice by searching for statistical regularities in their choice and reward history. If mice remained unpredictable against