Control Flow in Active Inference Systems—Part I: Classical and Quantum Formulations of Active Inference

IEEE Transactions on Molecular Biological and Multi-Scale Communications, Год журнала: 2023, Номер 9(2), С. 235 - 245

Опубликована: Май 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 this Part I, we introduce 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. 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.

Язык: Английский

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Federated inference and belief sharing

Neuroscience & Biobehavioral Reviews, Год журнала: 2023, Номер 156, С. 105500 - 105500

Опубликована: Дек. 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.

Язык: Английский

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The free energy principle induces intracellular compartmentalization

Biochemical and Biophysical Research Communications, Год журнала: 2024, Номер 723, С. 150070 - 150070

Опубликована: Май 7, 2024

Язык: Английский

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Artificial consciousness: a perspective from the free energy principle

Philosophical Studies, Год журнала: 2024, Номер 181(8), С. 1947 - 1970

Опубликована: Июнь 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.

Язык: Английский

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An Overview of Neurophenomenological Approaches to Meditation and their Relevance to Clinical Research

Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 1, 2024

Язык: Английский

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Deep computational neurophenomenology: A methodological framework for investigating the how of experience

Опубликована: Фев. 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.

Язык: Английский

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Sustainability under Active Inference

Systems, Год журнала: 2024, Номер 12(5), С. 163 - 163

Опубликована: Май 4, 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 an agent part collective. start by connecting with well-being, building on existing 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 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 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.

Язык: Английский

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Sustainability under Active Inference

Опубликована: Май 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.

Язык: Английский

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An overview of neurophenomenological approaches to meditation and their relevance to clinical research

Опубликована: Июнь 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.

Язык: Английский

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Making the Thermodynamic Cost of Active Inference Explicit

Entropy, Год журнала: 2024, Номер 26(8), С. 622 - 622

Опубликована: Июль 24, 2024

When describing Active Inference Agents (AIAs), the term "energy" can have two distinct meanings. One is energy that utilized by AIA (e.g., electrical or chemical energy). The second meaning so-called Variational Free Energy (VFE), a statistical quantity which provides an upper bound on surprisal. In this paper, we develop account of former quantity-the Thermodynamic (TFE)-and its relationship with latter. We highlight necessary tradeoffs between these in generic, quantum information-theoretic formulation, and macroscopic consequences those for ways organisms approach their environments. By making tradeoff explicit, provide theoretical basis different metabolic strategies from plants to predators use survive.

Язык: Английский

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