ArticleEntropy (Basel, Switzerland)2021
An Active Inference Model of Collective Intelligence.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 28 citations in OpenAlex.
- The Game of Self: Identity and Experience as Active Inference.Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc · 2026Article
- Intermittent Active Inference.Entropy (Basel, Switzerland) · 2026Article
- Decision, Inference, and Information: Formal Equivalences Under Active Inference.Entropy (Basel, Switzerland) · 2025Review
- Why collective behaviours self-organize to criticality: a primer on information-theoretic and thermodynamic utility measures.Royal Society open science · 2025Article
- Fostering Collective Intelligence in Human-AI Collaboration: Laying the Groundwork for COHUMAIN.Topics in cognitive science · 2025Article
- As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference.Entropy (Basel, Switzerland) · 2025Article
- Collective behavior from surprise minimization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Federated inference and belief sharing.Neuroscience and biobehavioral reviews · 2024Review
- Collective predictive coding hypothesis: symbol emergence as decentralized Bayesian inference.Frontiers in robotics and AI · 2024Article
- Applying the Free Energy Principle to Complex Adaptive Systems.Entropy (Basel, Switzerland) · 2022Article
- Epistemic Communities under Active Inference.Entropy (Basel, Switzerland) · 2022Article
- Dynamic Expectation Maximization Algorithm for Estimation of Linear Systems with Colored Noise.Entropy (Basel, Switzerland) · 2021Article
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Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Collective intelligence, an emergent phenomenon in which a composite system of multiple interacting agents performs at levels greater than the sum of its parts, has long compelled research efforts in social and behavioral sciences. To date, however, formal models of collective intelligence have lacked a plausible mathematical description of the relationship between local-scale interactions between autonomous sub-system components (individuals) and global-scale behavior of the composite system (the collective). In this paper we use the Active Inference Formulation (AIF), a framework for explaining the behavior of any non-equilibrium steady state system at any scale, to posit a minimal agent-based model that simulates the relationship between local individual-level interaction and collective intelligence. We explore the effects of providing baseline AIF agents (Model 1) with specific cognitive capabilities: Theory of Mind (Model 2), Goal Alignment (Model 3), and Theory of Mind with Goal Alignment (Model 4). These stepwise transitions in sophistication of cognitive ability are motivated by the types of advancements plausibly required for an AIF agent to persist and flourish in an environment populated by other highly autonomous AIF agents, and have also recently been shown to map naturally to canonical steps in human cognitive ability. Illustrative results show that stepwise cognitive transitions increase system performance by providing complementary mechanisms for alignment between agents' local and global optima. Alignment emerges endogenously from the dynamics of interacting AIF agents themselves, rather than being imposed exogenously by incentives to agents' behaviors (contra existing computational models of collective intelligence) or top-down priors for collective behavior (contra existing multiscale simulations of AIF). These results shed light on the types of generic information-theoretic patterns conducive to collective intelligence in human and other complex adaptive systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.