Algorithmic Complexity in Minority Game

TL;DR

This paper applies algorithmic complexity, entropy, and information theory to analyze the Minority Game, revealing how agent memory influences the complexity and information content of game outcomes beyond traditional volatility measures.

Contribution

It introduces a novel approach using information-theoretic tools to study the complex behavior of the Minority Game, emphasizing the role of agent memory.

Findings

Physical complexity and mutual information depend on agent memory size.

These measures provide deeper insights into the game's complexity than volatility.

Memory size significantly influences the information content of game outcomes.

Abstract

In this paper we introduce a new approach for the study of the complex behavior of Minority Game using the tools of algorithmic complexity, physical entropy and information theory. We show that physical complexity and mutual information function strongly depend on memory size of the agents and yields more information about the complex features of the stream of binary outcomes of the game than volatility itself.