Nash equilibrium and evolutionary dynamics in semifinalists' dilemma

TL;DR

This paper analyzes strategic stamina allocation in a four-player tournament, identifying multiple Nash equilibrium phases based on payoff structures and employing evolutionary dynamics to understand the stability and behavior of these strategies.

Contribution

It provides a comprehensive characterization of symmetric Nash equilibria in a semifinalist dilemma with general payoffs and introduces evolutionary replicator dynamics analysis for dynamic insights.

Findings

Three phases of Nash equilibria identified based on payoff differences.

Pure strategies where all players invest fully or not at all are equilibria under certain conditions.

Evolutionary dynamics replicate Nash equilibria and reveal stability properties.

Abstract

We consider a tournament among four equally strong semifinalists. The players have to decide how much stamina to use in the semifinals, provided that the rest is available in the final and the third-place playoff. We investigate optimal strategies for allocating stamina to the successive matches when players' prizes (payoffs) are given according to the tournament results. From the basic assumption that the probability to win a match follows a nondecreasing function of stamina difference, we present symmetric Nash equilibria for general payoff structures. We find three different phases of the Nash equilibria in the payoff space. First, when the champion wins a much bigger payoff than the others, any pure strategy can constitute a Nash equilibrium as long as all four players adopt it in common. Second, when the first two places are much more valuable than the other two, the only Nash equilibrium is such that everyone uses a pure strategy investing all stamina in the semifinal. Third, when the payoff for last place is much smaller than the others, a Nash equilibrium is formed when every player adopts a mixed strategy of using all or none of its stamina in the semifinals. In a limiting case that only last place pays the penalty, this mixed-strategy profile can be proved to be a unique symmetric Nash equilibrium, at least when the winning probability follows a Heaviside step function. Moreover, by using this Heaviside step function, we study the tournament by using evolutionary replicator dynamics to obtain analytic solutions, which reproduces the corresponding Nash equilibria on the population level and gives information on dynamic aspects.