Systems of bounded rational agents with information-theoretic constraints

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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 a focus on fewer tasks, thus leading to a more efficient execution, but in turn, it 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.

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APA

Gottwald, S., & Braun, D. A. (2019, February 1). Systems of bounded rational agents with information-theoretic constraints. Neural Computation. MIT Press Journals. https://doi.org/10.1162/neco_a_01153

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