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Psychologists, cognitive scientists, computational psychiatry groups, and Institute fellows.
A research scaffold for cognition, affect, the self, social interaction, and computational psychiatry.
このページで
Active inference treats psychological constructs — perception, attention, emotion, motivation, the self, and social interaction — as inference and action under a generative model, giving psychology a shared formal language for phenomena usually studied in separate sub-disciplines.
Perception, affect, motivation, and selfhood can each be cast as inference problems: estimating hidden causes of sensory and interoceptive signals and acting to realise preferred states. The framework connects individual cognition to dyads and groups, and recasts psychopathology as aberrant priors, precision, or generative-model structure rather than isolated symptoms.
A domain report should distinguish generative models of cognition/affect/self, policy selection and motivation via expected free energy, interoception and emotion regulation, hierarchical models of control and social interaction, and learning as model revision (including psychotherapeutic change). The SPM and pymdp ecosystems provide the canonical computational scaffolding.
The next pass should separate reviewed theory from empirical and clinical work, and prioritise model validation, parameter identifiability, scaling from individuals to dyads and groups, and ethics/interpretability for clinical decision support. Experimental paradigms and datasets should be catalogued alongside the models they test.
Karl J. Friston (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience. DOI: 10.1038/nrn2787. Thomas Parr, Giovanni Pezzulo, Karl J. Friston (2022). Active Inference: The Free Energy Principle in Mind, Brain, and Behavior. MIT Press. Giovanni Pezzulo, Francesco Rigoli, Karl J. Friston (2017). Active Inference, homeostatic regulation and adaptive behavioural control. Progress in Neurobiology. DOI: 10.1016/j.pneurobio.2017.08.001. Maxwell J. D. Ramstead, Karl J. Friston, Axel Constant, Lancelot Da Costa, Casper Hesp, Beren Millidge, Alexander Tschantz (2023). On Bayesian Mechanics: A Physics of and by Beliefs. arXiv. Lancelot Da Costa, Thomas Parr, Noor Sajid, Sebastijan Veselic, Victorita Neacsu, Karl J. Friston (2020). Active inference on discrete state-spaces: A synthesis. Journal of Mathematical Psychology. DOI: 10.1016/j.jmp.2020.102447.
キーの表面
Represent attention, emotion, motivation, and the self as coupled inference-and-action processes.
Model disorders as aberrant priors, precision-weighting, or generative-model structure, with explicit uncertainty.
Separate reviewed theory, simulation, and empirical/clinical evidence on every public page.
関連リソース
外部リンクは共有レジストリから解決されるため、訪問者向け目的地は中央集権的かつ確認可能な状態が保たれます。
Audience: Researcher
Public ecosystem shortlink for Institute context, projects, activities, and conceptual maps.
Audience: Developer
Public GitHub organization for Institute repositories and open-source work.
Audience: Developer
Project repository for multiagent Active Inference modeling work.
Audience: Developer
Generalized Notation Notation project repository for model communication.
Audience: Developer
Geospatial modeling repository connected to ecological and bioregional applications.
Audience: Researcher
Research and publication-oriented repository for the Active Inference Journal.
Audience: Contributor
Public Project Preparation shortlink for making proposed work legible and actionable.
Audience: Contributor
Public project measurement shortlink for reporting progress and outputs.
Audience: Researcher
Public Active Inference Ontology shortlink for shared conceptual infrastructure.
Audience: Researcher
External paper repository surfaced from the official research page.
Audience: Researcher
Reachable arXiv reference surfaced from the official research page.
Audience: Researcher
Reachable arXiv reference surfaced from the official research page.
公式ページ
Audience: Researcher
Official research entry point, currently resolving to the research overview.
Audience: Researcher
Official research overview page.
Audience: Developer
Official Knowledge Engineering page.
Audience: Developer
Official Active Blockference page.
Audience: Researcher
Official theoretical neurobiology page.
Audience: Contributor
Public projects shortlink for project directories and activity-linked work.
Audience: Contributor
Public project measurement shortlink for reporting progress and outputs.
Audience: Researcher
Public Active Inference Ontology shortlink for shared conceptual infrastructure.
リポジトリ
Audience: Researcher
Computational meta-analysis of Active Inference literature with nanopublication and knowledge-graph outputs.
Audience: Researcher
Ontology-oriented repository for shared Active Inference concepts and decentralized science knowledge infrastructure.
Audience: Developer
Notebook-based applied Active Inference work connected to blockchain-adjacent and generative modeling examples.
Audience: Developer
Python models and materials for ant-inspired multiagent Active Inference.
Audience: Researcher
Active Inference & Category Theory
Audience: Researcher
Public content repository for the Active Inference Journal and related publication infrastructure.
Audience: Researcher
Active Entity Ontology for Science
Audience: Developer
Public ants repository in the ActiveInferenceInstitute GitHub namespace.