Smart Transformations: The Evolution of Choice Principles

TL;DR

This paper explores how different subjective payoff transformations evolve across a class of games, showing that regret minimization can outperform payoff maximization under uncertainty in symmetric 2x2 games.

Contribution

It extends evolutionary game theory by analyzing the evolution of payoff conceptualizations across multiple games, introducing the concept of meta-games.

Findings

Regret minimization can outperform payoff maximization.

Security strategies are effective under radical uncertainty.

Evolutionary success depends on the type of payoff transformation.

Abstract

Evolutionary game theory classically investigates which behavioral patterns are evolutionarily successful in a single game. More recently, a number of contributions have studied the evolution of preferences instead: which subjective conceptualizations of a game's payoffs give rise to evolutionarily successful behavior in a single game. Here, we want to extend this existing approach even further by asking: which general patterns of subjective conceptualizations of payoff functions are evolutionarily successful across a class of games. In other words, we will look at evolutionary competition of payoff transformations in "meta-games", obtained from averaging over payoffs of single games. Focusing for a start on the class of 2x2 symmetric games, we show that regret minimization can outperform payoff maximization if agents resort to a security strategy in case of radical uncertainty.