Self-supervision, normativity and the free energy principle.
The free energy principle says that any self-organising system that is at nonequilibrium steady-state with its environment must minimize its (variational) free energy. It is proposed as a grand unifying principle for cognitive science and biology. The principle can appear cryptic, esoteric, too ambi...
| Publicado en: | Synthese Vol. 199; no. 1/2; pp. 29 - 54 |
|---|---|
| Autor principal: | |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2021
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=153650773&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 153650773 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2021 vid: 199 iid: 1/2 pid: 237 pub: Springer Nature artinfo: ui: 153650773 10.1007/s11229-020-02622-2 ppf: 29 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: P size: 447KB tig: atl: Self-supervision, normativity and the free energy principle. aug: au: Hohwy, Jakob affil: Cognition and Philosophy Lab, Philosophy Department, School of Philosophical, Historical and International Studies, 20 Chancellors Walk, Room E674, Monash University, 3800, Clayton, VIC, Australia su: Normativity (Ethics) Cognitive science Phenomenological biology Mathematical analysis Machine learning Supervised learning sug: subj: Normativity (Ethics) Cognitive science Phenomenological biology Mathematical analysis Machine learning Supervised learning keyword: Active inference Free energy principle Normativity Predictive processing Principles Process theories Self-evidencing Self-organisation Self-supervision Unsupervised learning ab: The free energy principle says that any self-organising system that is at nonequilibrium steady-state with its environment must minimize its (variational) free energy. It is proposed as a grand unifying principle for cognitive science and biology. The principle can appear cryptic, esoteric, too ambitious, and unfalsifiable—suggesting it would be best to suspend any belief in the principle, and instead focus on individual, more concrete and falsifiable 'process theories' for particular biological processes and phenomena like perception, decision and action. Here, I explain the free energy principle, and I argue that it is best understood as offering a conceptual and mathematical analysis of the concept of existence of self-organising systems. This analysis offers a new type of solution to long-standing problems in neurobiology, cognitive science, machine learning and philosophy concerning the possibility of normatively constrained, self-supervised learning and inference. The principle can therefore uniquely serve as a regulatory principle for process theories, to ensure that process theories conforming to it enable self-supervision. This is, at least for those who believe self-supervision is a foundational explanatory task, good reason to believe the free energy principle. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2021. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
|---|