Systems of bounded rational agents with information-theoretic constraints

TL;DR

This paper introduces an information-theoretic framework to explain how bounded rationality leads to specialization and hierarchical organization in systems, optimizing efficiency under information-processing constraints.

Contribution

It proposes a Free Energy-based approach to analyze bounded rational agents, demonstrating that hierarchical specialization optimizes system efficiency given information constraints.

Findings

Hierarchical structures emerge as optimal under information limitations.

Specialization reduces task complexity and enhances efficiency.

Coordination among specialized units is essential for optimal performance.

Abstract

Specialization and hierarchical organization are important features of efficient collaboration in economical, artificial, and biological systems. Here, we investigate the hypothesis that both features can be explained by the fact that each entity of such a system is limited in a certain way. We propose an information-theoretic approach based on a Free Energy principle, in order to computationally analyze systems of bounded rational agents that deal with such limitations optimally. We find that specialization allows to focus on fewer tasks, thus leading to a more efficient execution, but in turn requires coordination in hierarchical structures of specialized experts and coordinating units. Our results suggest that hierarchical architectures of specialized units at lower levels that are coordinated by units at higher levels are optimal, given that each unit's information-processing capability is limited and conforms to constraints on complexity costs.