Reflexion in mathematical models of decision-making

TL;DR

This paper introduces a generalized framework for mathematical models of decision-making that incorporates reflexive beliefs about nature, opponents, and decision principles within game theory, collective behavior, and learning contexts.

Contribution

It extends static and dynamic models by explicitly modeling reflexive beliefs, providing a more comprehensive understanding of decision-making processes.

Findings

Reflexive models enhance understanding of strategic behavior.

Incorporating beliefs about opponents improves predictive accuracy.

The framework unifies various decision-making theories.

Abstract

The paper is devoted to a generalization of static and dynamic mathematical models of behavior with explicitly stated reflexive models of agents' decision-making. Reflexion is considered as agent's beliefs about nature, opponents' beliefs and opponents' decision-making principles in the framework of game theory, collective behavior theory and learning models.