Resilience and active inference

Autor: Mark Miller, Mahault Albarracin, Riddhi J. Pitliya, Alex Kiefer, Jonas Mago, Claire Gorman, Karl J. Friston, Maxwell J. D. Ramstead
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Psychology, Vol 13 (2022)
Druh dokumentu: article
ISSN: 1664-1078
DOI: 10.3389/fpsyg.2022.1059117
Popis: In this article, we aim to conceptualize and formalize the construct of resilience using the tools of active inference, a new physics-based modeling approach apt for the description and analysis of complex adaptive systems. We intend this as a first step toward a computational model of resilient systems. We begin by offering a conceptual analysis of resilience, to clarify its meaning, as established in the literature. We examine an orthogonal, threefold distinction between meanings of the word “resilience”: (i) inertia, or the ability to resist change (ii) elasticity, or the ability to bounce back from a perturbation, and (iii) plasticity, or the ability to flexibly expand the repertoire of adaptive states. We then situate all three senses of resilience within active inference. We map resilience as inertia onto high precision beliefs, resilience as elasticity onto relaxation back to characteristic (i.e., attracting) states, and resilience as plasticity onto functional redundancy and structural degeneracy.
Databáze: Directory of Open Access Journals