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Systems of Bounded Rational Agents with Information-Theoretic Constraints
Sebastian Gottwald1, Daniel A Braun2
1Institute of Neural Information Processing, Faculty of Engineering, Computer Science and Psychology, University of Ulm, Ulm, Baden-Württemberg, 89081 Germany sebastian.gottwald@uni-ulm.de.
Specialization and hierarchy in systems arise from entity limitations. Optimal collaboration emerges from bounded rational agents managing these constraints, leading to efficient, coordinated structures.
Area of Science:
- Complexity Science
- Systems Biology
- Artificial Intelligence
Background:
- Efficient collaboration in economical, artificial, and biological systems often exhibits specialization and hierarchical organization.
- These organizational features are hypothesized to stem from inherent limitations within individual entities of these systems.
Purpose of the Study:
- To investigate the hypothesis that limitations drive specialization and hierarchical organization in collaborative systems.
- To computationally analyze systems of bounded rational agents using an information-theoretic approach based on the free energy principle.
Main Methods:
- Information-theoretic analysis
- Free energy principle
- Computational modeling of bounded rational agents
Main Results:
- Specialization enhances task efficiency by allowing focus but necessitates coordination.
- Hierarchical structures with specialized lower levels and coordinating higher levels are found to be optimal.
- Optimal architectures are contingent upon limited information-processing capabilities and complexity cost constraints.
Conclusions:
- Limitations are a fundamental driver for specialization and hierarchical organization in complex systems.
- The free energy principle provides a framework for understanding optimal coordination strategies under constraints.
- Hierarchical specialization offers an efficient collaborative solution for systems with bounded agents.
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