The evolutionary minority game with local coordination

TL;DR

This paper explores a modified evolutionary minority game where agents use local neighborhood information for decision-making, revealing that local coordination can improve overall system performance compared to global strategies.

Contribution

It introduces a local interaction framework into the EMG and demonstrates that local decision-making can lead to better coordination than global approaches.

Findings

Local information improves coordination in EMG

Better system performance with neighborhood-based updates

Surprising effectiveness of local over global strategies

Abstract

We discuss a modification of the Evolutionary Minority Game (EMG) in which agents are placed in the nodes of a regular or a random graph. A neighborhood for each agent can thus be defined and a modification of the usual relaxation dynamics can be made in which each agent updates her decision scheme depending upon the options made in her neighborhood. We report numerical results for the topologies of a ring, a torus and a random graph changing the size of the neighborhood. We find the surprising result that in the EMG a better coordination (a lower frustration) can be achieved if all agents base their actions on local information disregarding the global trend in the self-segregation process.