Control Flow in Active Inference Systems—Part II: Tensor Networks as General Models of Control Flow DOI
Chris Fields, Filippo Fabrocini, Karl Friston

et al.

IEEE Transactions on Molecular Biological and Multi-Scale Communications, Journal Year: 2023, Volume and Issue: 9(2), P. 246 - 256

Published: May 1, 2023

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception action resources in context specific way. In Part I, we introduced the principle (FEP) idea of active inference as Bayesian prediction-error minimization, show how problem arises systems. We then review classical quantum formulations FEP, with former being limit latter. this accompanying II, when are described executing driven by their flow always be represented tensor networks (TNs). TNs implemented within general framework topological neural networks, discuss implications results for modeling biological at multiple scales.

Language: Английский

Federated inference and belief sharing DOI Creative Commons
Karl Friston, Thomas Parr, Conor Heins

et al.

Neuroscience & Biobehavioral Reviews, Journal Year: 2023, Volume and Issue: 156, P. 105500 - 105500

Published: Dec. 5, 2023

This paper concerns the distributed intelligence or federated inference that emerges under belief-sharing among agents who share a common world-and world model. Imagine, for example, several animals keeping lookout predators. Their collective surveillance rests upon being able to communicate their beliefs-about what they see-among themselves. But, how is this possible? Here, we show all necessary components arise from minimising free energy. We use numerical studies simulate generation, acquisition and emergence of language in synthetic agents. Specifically, consider inference, learning selection as variational energy posterior (i.e., Bayesian) beliefs about states, parameters structure generative models, respectively. The theme-that attends these optimisation processes-is actions minimise expected energy, leading active model (a.k.a., learning). first illustrate role communication resolving uncertainty latent states partially observed world, on which have complementary perspectives. then requisite language-entailed by likelihood mapping an agent's overt expression (e.g., speech)-showing can be transmitted across generations learning. Finally, emergent property minimisation, when operate within same econiche. conclude with discussion various perspectives phenomena; ranging cultural niche construction, through learning, complexity ensembles self-organising systems.

Language: Английский

Citations

16

The free energy principle induces intracellular compartmentalization DOI
Chris Fields

Biochemical and Biophysical Research Communications, Journal Year: 2024, Volume and Issue: 723, P. 150070 - 150070

Published: May 7, 2024

Language: Английский

Citations

5

Deep computational neurophenomenology: A methodological framework for investigating the how of experience DOI Open Access
Lars Sandved-Smith, Juan Diego Bogotá, Jakob Hohwy

et al.

Published: Feb. 28, 2024

The context for our paper comes from the neurophenomenology research program initiated by Francisco Varela at end of 1990s. Varela’s working hypothesis was that, to be successful, a consciousness must progress relating first-person phenomenological accounts structure experience and their third-person counterparts in neuroscience through reciprocal or mutual constraints. Leveraging Bayesian mechanics, particular deep parametric active inference, we demonstrate potential epistemically advantageous constraints between phenomenological, computational, behavioural physiological vocabularies. Specifically, dual information geometry mechanics serves establish, under certain conditions, generative passages lived its instantiation. This argues epistemological necessity such inclusion trained reflective awareness neurophenomenological empirical approaches, showcasing incremental epistemic gains that come shifting focus contents (i.e. what subject experiences given experimental set-up) how - activities allow meaningful world appear us as experience. explanatory power resulting framework, computational neurophenomenology, arises disciplined circulation first perspectives enabled formalism where depth refers property models can form beliefs about parameters own modelling process. Hence, this contributes understanding bridging descriptions instantiations, whilst also highlighting significance person investigation protocols.

Language: Английский

Citations

4

Artificial consciousness: a perspective from the free energy principle DOI Creative Commons
Wanja Wiese

Philosophical Studies, Journal Year: 2024, Volume and Issue: 181(8), P. 1947 - 1970

Published: June 26, 2024

Abstract Does the assumption of a weak form computational functionalism, according to which right neural computation is sufficient for consciousness, entail that digital simulation such computations conscious? Or must this be implemented in way, order replicate consciousness? From perspective Karl Friston’s free energy principle, self-organising systems (such as living organisms) share set properties could realised artificial systems, but are not instantiated by computers with classical (von Neumann) architecture. I argue at least one these properties, viz. certain kind causal flow, can used draw distinction between merely simulate, and those actually consciousness.

Language: Английский

Citations

4

An Overview of Neurophenomenological Approaches to Meditation and their Relevance to Clinical Research DOI Creative Commons
Antoine Lutz, Oussama Abdoun, Yair Dor‐Ziderman

et al.

Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Citations

4

Triple equivalence for the emergence of biological intelligence DOI Creative Commons
Takuya Isomura

Communications Physics, Journal Year: 2025, Volume and Issue: 8(1)

Published: April 15, 2025

Language: Английский

Citations

0

Sustainability under Active Inference DOI Open Access
Mahault Albarracin, Maxwell J. D. Ramstead, Riddhi J. Pitliya

et al.

Published: May 2, 2024

In this paper we explore the known connection among sustainability, resilience, and well-being within framework of active inference. Initially, revisit how notions resilience intersect inference before defining sustainability. We adopt a holistic concept sustainability denoting enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth encompass community networks, labor, knowledge. Using Free Energy Principle, can emphasize role fostering resource renewal, harmonious system-entity exchanges, practices that encourage self-organization as pathways achieving both in an agent collectives. start by connecting Active Inference with well-being, building on exsiting work. then attempt link asserting alone is insufficient for sustainable outcomes. While absorbing shocks stresses, must be intrinsically linked ensure adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes address root causes unsustainability. Sustainability, therefore, manifest across extended timescales all system strata, from individual components broader system, uphold ecological integrity, economic stability, social well-being. explain manifests at level agent, collectives systems. To model quantify interdependencies between resources their impact overall introduce application network theory dynamical systems theory. optimization precision or learning rates through framework, advocating approach fosters elastic plastic necessary long-term abundance.

Language: Английский

Citations

3

An overview of neurophenomenological approaches to meditation and their relevance to clinical research DOI Open Access
Antoine Lutz, Oussama Abdoun, Yair Dor‐Ziderman

et al.

Published: June 11, 2024

There is a renewed interest in taking phenomenology seriously consciousness research, contemporary psychiatry, and neurocomputation. The neurophenomenology research program, pioneered by Varela (1996), rigorously examines subjective experience using first-person methodologies inspired contemplative practices. This review explores recent advancements neurophenomenological approaches, particularly their application to meditation practices potential clinical translations. We first examine innovative multi-dimensional phenomenological assessment tools designed capture subtle, dynamic shifts experiential contents structures of during meditation. These sampling approaches allow shedding new light on the mechanisms trajectories practice retreat. Secondly, we highlight how empirical studies leverage expertise experienced meditators deconstruct aversive self-related processes, providing detailed reports that guide researchers identifying novel behavioral neurodynamic markers associated with pain regulation, self-dissolution acceptance mortality. Finally, discuss framework, deep computational neurophenomenology, which updates theoretical ambitions “naturalize phenomenology” (Varela, 1997). framework uses formalism parametric active inference, where depth refers property generative models can form beliefs about parameters own modeling process. Collectively, these methodological innovations, centered around rigorous investigation, epistemologically beneficial mutual constraints among phenomenological, computational, neurophysiological domains. could contribute an integrated understanding biological basis mental illness, its treatment tight connections lived patient.

Language: Английский

Citations

3

Action of the Euclidean versus projective group on an agent’s internal space in curiosity driven exploration DOI Creative Commons
Grégoire Sergeant-Perthuis,

Nils Ruet,

Dimitri Ognibene

et al.

Biological Cybernetics, Journal Year: 2025, Volume and Issue: 119(1)

Published: Jan. 17, 2025

Language: Английский

Citations

0

As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference DOI Creative Commons
Peter Thestrup Waade, C. Olesen, Jonathan Ehrenreich Laursen

et al.

Entropy, Journal Year: 2025, Volume and Issue: 27(2), P. 143 - 143

Published: Feb. 1, 2025

Active inference under the Free Energy Principle has been proposed as an across-scales compatible framework for understanding and modelling behaviour self-maintenance. Crucially, a collective of active agents can, if they maintain group-level Markov blanket, constitute larger agent with generative model its own. This potential computational scale-free structures speaks to application self-organizing systems across spatiotemporal scales, from cells human collectives. Due difficulty reconstructing that explains emergent agents, there little research on this kind multi-scale inference. Here, we propose data-driven methodology characterising relation between dynamics constituent individual agents. We apply methods cognitive psychiatry, applicable well other types approaches. Using simple Multi-Armed Bandit task example, employ new ActiveInference.jl library Julia simulate who are equipped blanket. use sampling-based parameter estimation make inferences about agent, show is non-trivial relationship models constitute, even in setting. Finally, point number ways which might be applied better understand relations nested scales.

Language: Английский

Citations

0