Automata-based Adaptive Behavior for Economical Modelling Using Game Theory

TL;DR

This paper introduces an automata-based approach using genetic automata and matrix representations to model adaptive strategies in economic game theory, enabling the analysis of emergent systems of strategic entities.

Contribution

It presents a novel automata formalism with matrix representation for modeling adaptive strategies in economic game theory, facilitating the analysis of emergent behaviors.

Findings

Automata-based formalism effectively models adaptive strategies.

Matrix representation enables computation of strategy semi-distances.

Automated processes generate emergent systems of strategic entities.

Abstract

In this chapter, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to build adaptive strategies for the players. We explain how the automata-based formalism proposed - matrix representation of automata with multiplicities - allows to define semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata.