Federated inference and belief sharing

Catalog Row36

Citation KeyFriedman2024FederatedInferenceBeliefSharing036

Paper FolderAvailable

DOI10.1016/j.neubiorev.2023.105500

Overview

Extracted from the local paper documentation when available.

This paper explores federated inference and belief-sharing among agents in a shared environment, demonstrating how communication and language can emerge from minimizing free energy. Through simulations, it illustrates the processes of inference, learning, and model selection that facilitate collective intelligence and the development of language.

federated inferencebelief sharingActive Inferencedistributed intelligencemulti-agent systemsmessage passingcollective cognitionprivacy-preserving inference

Use Notes

Concise findings and methods pulled from README/SKILL documentation.

Findings / Concepts

Introduces the concept of federated inference through belief-sharing among agents.
Demonstrates the emergence of language as a byproduct of free energy minimization.
Provides a framework for understanding collective intelligence in ensembles of agents.
Explores the implications of belief-sharing for cultural niche construction and complexity in self-organizing systems.

Methods / Techniques

Utilizes numerical simulations to model belief-sharing and active inference among synthetic agents.
Applies the free energy principle to describe the dynamics of belief updating and communication.
Examines the acquisition of language through active learning and the transmission of beliefs across generations.
Employs Bayesian model selection to illustrate structure learning in generative models.

Citation

Plain-text citation for quick reuse.

Friedman, Daniel Ari. 2024. Federated inference and belief sharing. Neuroscience & Biobehavioral Reviews.

Primary source Documentation BibTeX