ArticleJournal of theoretical biology2018
Free-energy minimization in joint agent-environment systems: A niche construction perspective.
Article in Journal of theoretical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
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- Resilience phenotypes derived from an active inference account of allostasis.Frontiers in behavioral neuroscience · 2025Article
- Shifting boundaries, extended minds: ambient technology and extended allostatic control.Synthese · 2025Article
- An Active-Inference Approach to Second-Person Neuroscience.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Review
- A computational approach to selective attention in embodied approaches to cognitive archaeology.Journal of the Royal Society, Interface · 2024Review
- Active Inference and Social Actors: Towards a Neuro-Bio-Social Theory of Brains and Bodies in Their Worlds.Kolner Zeitschrift fur Soziologie und Sozialpsychologie · 2024Article
- Federated inference and belief sharing.Neuroscience and biobehavioral reviews · 2024Review
- Bio-Inspired Intelligent Systems: Negotiations between Minimum Manifest Task Entropy and Maximum Latent System Entropy in Changing Environments.Entropy (Basel, Switzerland) · 2023Article
- A Variational Synthesis of Evolutionary and Developmental Dynamics.Entropy (Basel, Switzerland) · 2023Article
- Adversarial inference: predictive minds in the attention economy.Neuroscience of consciousness · 2023Article
- Extended active inference: Constructing predictive cognition beyond skulls.Mind & language · 2022Article
- Organizational Neuroscience of Industrial Adaptive Behavior.Behavioral sciences (Basel, Switzerland) · 2022Article
- Metacognition as a Consequence of Competing Evolutionary Time Scales.Entropy (Basel, Switzerland) · 2022Article
- The Free Energy Principle for Perception and Action: A Deep Learning Perspective.Entropy (Basel, Switzerland) · 2022Review
- The evolution of brain architectures for predictive coding and active inference.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Synchronous Generative Development amidst Situated Entropy.Entropy (Basel, Switzerland) · 2022Article
- Neural Synchrony and Network Dynamics in Social Interaction: A Hyper-Brain Cell Assembly Hypothesis.Frontiers in human neuroscience · 2022Article
- Integrating Evolutionary, Cultural, and Computational Psychiatry: A Multilevel Systemic Approach.Frontiers in psychiatry · 2022Article
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5 authors.
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Abstract
The free-energy principle is an attempt to explain the structure of the agent and its brain, starting from the fact that an agent exists (Friston and Stephan, 2007; Friston et al., 2010). More specifically, it can be regarded as a systematic attempt to understand the 'fit' between an embodied agent and its niche, where the quantity of free-energy is a measure for the 'misfit' or disattunement (Bruineberg and Rietveld, 2014) between agent and environment. This paper offers a proof-of-principle simulation of niche construction under the free-energy principle. Agent-centered treatments have so far failed to address situations where environments change alongside agents, often due to the action of agents themselves. The key point of this paper is that the minimum of free-energy is not at a point in which the agent is maximally adapted to the statistics of a static environment, but can better be conceptualized an attracting manifold within the joint agent-environment state-space as a whole, which the system tends toward through mutual interaction. We will provide a general introduction to active inference and the free-energy principle. Using Markov Decision Processes (MDPs), we then describe a canonical generative model and the ensuing update equations that minimize free-energy. We then apply these equations to simulations of foraging in an environment; in which an agent learns the most efficient path to a pre-specified location. In some of those simulations, unbeknownst to the agent, the 'desire paths' emerge as a function of the activity of the agent (i.e. niche construction occurs). We will show how, depending on the relative inertia of the environment and agent, the joint agent-environment system moves to different attracting sets of jointly minimized free-energy.
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