Searching good strategies in adaptive minority games

TL;DR

This paper explores how genetic algorithm-based adaptation mechanisms influence agent strategies in minority games, leading to increased competition and improved collective utility in complex systems.

Contribution

It introduces a genetic algorithm-based adaptation approach in minority games and analyzes its effects on system dynamics and individual agent performance.

Findings

Adaptation tightens competition among agents.

System tends toward states with higher collective utility.

Different adaptation mechanisms expand minority games' applicability.

Abstract

In this paper we introduce adaptation mechanism based on genetic algorithms in minority games. If agents find their performances too low, they modify their strategies in hope to improve their performances and become more successful. One aim of this study is to find out what happens at the system as well as at the individual agent level. We observe that adaptation remarkably tightens the competition among the agents, and tries to pull the collective system into a state where the aggregate utility is the largest. We first make a brief comparative study of the different adaptation mechanisms and then present in more detail parametric studies. These different adaptation mechanisms broaden the scope of the applications of minority games to the study of complex systems.