scholarly journals Accessing Active Inference Theory through Its Implicit and Deliberative Practice in Human Organizations

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1521
Author(s):  
Stephen Fox
Keyword(s):  
Lived Experience ◽  
Public Institutions ◽  
Active Inference ◽  
Energy Principle ◽  
Private Companies ◽  
Free Energy Principle ◽  
Starting Point ◽  
And Mathematics ◽  
Autopoietic Organization ◽  
Inference Theory

Active inference theory (AIT) is a corollary of the free-energy principle, which formalizes cognition of living system’s autopoietic organization. AIT comprises specialist terminology and mathematics used in theoretical neurobiology. Yet, active inference is common practice in human organizations, such as private companies, public institutions, and not-for-profits. Active inference encompasses three interrelated types of actions, which are carried out to minimize uncertainty about how organizations will survive. The three types of action are updating work beliefs, shifting work attention, and/or changing how work is performed. Accordingly, an alternative starting point for grasping active inference, rather than trying to understand AIT specialist terminology and mathematics, is to reflect upon lived experience. In other words, grasping active inference through autoethnographic research. In this short communication paper, accessing AIT through autoethnography is explained in terms of active inference in existing organizational practice (implicit active inference), new organizational methodologies that are informed by AIT (deliberative active inference), and combining implicit and deliberative active inference. In addition, these autoethnographic options for grasping AIT are related to generative learning.

scholarly journals What is mood? A computational perspective

2018 ◽  
Vol 48 (14) ◽  
pp. 2277-2284 ◽  
Author(s):  
James E Clark ◽  
Stuart Watson ◽  
Karl J Friston
Keyword(s):  
Mood Disorders ◽  
Active Inference ◽  
Simple Formulation ◽  
Energy Principle ◽  
Free Energy Principle ◽  
New Approach ◽  
Functional Brain ◽  
Bayesian Brain ◽  
Multiple Levels ◽  
Computational Pathology

AbstractThe neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of – or certainty about – the predicted sensorimotor/interoceptive consequences of action. By extending this reasoning, in a hierarchical setting, we suggest mood states act as (hyper) priors over uncertainty (i.e. emotions). Here, we consider the same computational pathology in the proprioceptive and interoceptive (behavioural and autonomic) domain in order to furnish an explanation for mood disorders. This formulation reconciles several strands of research at multiple levels of enquiry.

scholarly journals ‘Through others we become ourselves’: The dialectics of predictive coding and active inference

2019 ◽  
Author(s):  
Dimitris Bolis ◽  
Leonhard Schilbach
Keyword(s):  
Free Energy ◽  
Social Interaction ◽  
Predictive Coding ◽  
Real Life ◽  
Other Minds ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Multiscale Dynamics ◽  
Cultural Processes

Thinking Through Other Minds (TTOM) creatively situates the free energy principle within real-life cultural processes, thereby enriching both sociocultural theories and Bayesian accounts of cognition. Here, shifting the attention from thinking to becoming, we suggest complementing such an account by focusing on the empirical, computational and conceptual investigation of the multiscale dynamics of social interaction.

scholarly journals Natural language syntax complies with the free-energy principle

2021 ◽  
Author(s):  
Elliot Murphy ◽  
Emma Holmes ◽  
Karl Friston
Keyword(s):  
Free Energy ◽  
Natural Language ◽  
Explanatory Power ◽  
Speech Segmentation ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Language Functions ◽  
Theoretical Syntax ◽  
Natural Language Syntax

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating elementary syntactic objects. We argue that recently proposed principles of economy in language design—such as “minimal search” and “least effort” criteria from theoretical syntax—adhere to the FEP. This permits a greater degree of explanatory power to the FEP—with respect to higher language functions—and presents linguists with a grounding in first principles of notions pertaining to computability. More generally, we explore the possibility of migrating certain topics in linguistics over to the domain of fields that investigate the FEP, such as complex polysemy. We aim to align concerns of linguists with the normative model for organic self-organisation associated with the FEP, marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference.

scholarly journals Integrated World Modeling Theory (IWMT) Implemented: Towards Reverse Engineering Consciousness with the Free Energy Principle and Active Inference

2020 ◽  
Author(s):  
Adam Safron
Keyword(s):  
Free Energy ◽  
Reference Frames ◽  
Phenomenal Consciousness ◽  
Predictive Processing ◽  
Active Inference ◽  
Perceptual Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
World Modeling ◽  
Modeling Theory

Integrated World Modeling Theory (IWMT) is a synthetic model that attempts to unify theories of consciousness within the Free Energy Principle and Active Inference framework, with particular emphasis on Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNWT). IWMT further suggests predictive processing in sensory hierarchies may be well-modeled as (folded, sparse, partially disentangled) variational autoencoders, with beliefs discretely-updated via the formation of synchronous complexes—as self-organizing harmonic modes (SOHMs)—potentially entailing maximal a posteriori (MAP) estimation via turbo coding. In this account, alpha-synchronized SOHMs across posterior cortices may constitute the kinds of maximal complexes described by IIT, as well as samples (or MAP estimates) from multimodal shared latent space, organized according to egocentric reference frames, entailing phenomenal consciousness as mid-level perceptual inference. When these posterior SOHMs couple with frontal complexes, this may enable various forms of conscious access as a kind of mental act(ive inference), affording higher order cognition/control, including the kinds of attentional/intentional processing and reportability described by GNWT. Across this autoencoding heterarchy, intermediate-level beliefs may be organized into spatiotemporal trajectories by the entorhinal/hippocampal system, so affording episodic memory, counterfactual imaginings, and planning.

scholarly journals Combining Active Inference and Hierarchical Predictive Coding: A Tutorial Introduction and Case Study

2019 ◽  
Author(s):  
Beren Millidge
Keyword(s):  
Free Energy ◽  
Reinforcement Learning ◽  
Predictive Coding ◽  
Action Selection ◽  
Proof Of Concept ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Perceptual Model

This paper combines the active inference formulation of action (Friston, 2009) with hierarchical predictive coding models (Friston, 2003) to provide a proof-of-concept implementation of an active inference agent able to solve a common reinforcement learning baseline -- the cart-pole environment in OpenAI gym. It demonstrates empirically that predictive coding and active inference approaches can be successfully scaled up to tasks more challenging than the mountain car (Friston 2009, 2012). We show that hierarchical predictive coding models can be learned from scratch during the task, and can successfully drive action selection via active inference. To our knowledge, it is the first implemented active inference agent to combine active inference with a hierarchical predictive coding perceptual model. We also provide a tutorial walk-through of the free-energy principle, hierarchical predictive coding, and active inference, including an in-depth derivation of our agent.

Social Active Inference

2021 ◽  
pp. 58-72
Author(s):  
El Hassan Bezzazi
Keyword(s):  
Free Energy ◽  
Real Life ◽  
Dynamic Logic ◽  
Negotiation Process ◽  
The Other ◽  
Optimal Decision ◽  
Embodied Perception ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle

The free energy principle and its corollary, active inference, were introduced by Karl Friston as an explanation embodied perception and action in neuroscience, and since, it has been used to address many other issues in different fields mainly related to cognitive science like learning, optimal decision, or interpersonal inference. Negotiation is a process where each negotiator has conflicting motivation is aiming to maximize his utility and where agreement is reached when the opposing interests are balanced. The purpose of this chapter is to illustrate how the free energy principle might be used through active inference in modeling a negotiation process based on an example of real life. The work is an attempt to bring together a dynamic logic framework with appropriate operators to consider motivation among agents on one hand and the active inference framework on the other hand.

scholarly journals Is the Free-Energy Principle a Formal Theory of Semantics? From Variational Density Dynamics to Neural and Phenotypic Representations

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 889 ◽  
Author(s):  
Maxwell J. D. Ramstead ◽  
Karl J. Friston ◽  
Inês Hipólito
Keyword(s):  
Free Energy ◽  
Formal Semantics ◽  
Formal Theory ◽  
Semantic Content ◽  
Active Inference ◽  
Explanatory Role ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Neural Representations ◽  
Internal States

The aim of this paper is twofold: (1) to assess whether the construct of neural representations plays an explanatory role under the variational free-energy principle and its corollary process theory, active inference; and (2) if so, to assess which philosophical stance—in relation to the ontological and epistemological status of representations—is most appropriate. We focus on non-realist (deflationary and fictionalist-instrumentalist) approaches. We consider a deflationary account of mental representation, according to which the explanatorily relevant contents of neural representations are mathematical, rather than cognitive, and a fictionalist or instrumentalist account, according to which representations are scientifically useful fictions that serve explanatory (and other) aims. After reviewing the free-energy principle and active inference, we argue that the model of adaptive phenotypes under the free-energy principle can be used to furnish a formal semantics, enabling us to assign semantic content to specific phenotypic states (the internal states of a Markovian system that exists far from equilibrium). We propose a modified fictionalist account—an organism-centered fictionalism or instrumentalism. We argue that, under the free-energy principle, pursuing even a deflationary account of the content of neural representations licenses the appeal to the kind of semantic content involved in the ‘aboutness’ or intentionality of cognitive systems; our position is thus coherent with, but rests on distinct assumptions from, the realist position. We argue that the free-energy principle thereby explains the aboutness or intentionality in living systems and hence their capacity to parse their sensory stream using an ontology or set of semantic factors.

scholarly journals A tale of two densities: active inference is enactive inference

2019 ◽  
Vol 28 (4) ◽  
pp. 225-239 ◽  
Author(s):  
Maxwell JD Ramstead ◽  
Michael D Kirchhoff ◽  
Karl J Friston
Keyword(s):  
Predictive Coding ◽  
Generative Models ◽  
Predictive Processing ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
The One ◽  
And Control ◽  
The Brain ◽  
Selection Of

The aim of this article is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) – and its corollary, active inference – in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature, because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain – variously known as predictive processing, predictive coding or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inference – what might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control – the self-organising, belief-guided selection of action policies – and do not have the properties ascribed by structural representationalists.

scholarly journals How mood tunes prediction: a neurophenomenological account of mood and its disturbance in major depression

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Julian Kiverstein ◽  
Mark Miller ◽  
Erik Rietveld
Keyword(s):  
Free Energy ◽  
Lived Experience ◽  
Cognitive Neuroscience ◽  
Energy Principle ◽  
Free Energy Principle ◽  
The World ◽  
The Future ◽  
Long Time ◽  
Future Consequences ◽  
Measure Of Uncertainty

Abstract In this article, we propose a neurophenomenological account of what moods are, and how they work. We draw upon phenomenology to show how mood attunes a person to a space of significant possibilities. Mood structures a person’s lived experience by fixing the kinds of significance the world can have for them in a given situation. We employ Karl Friston’s free-energy principle to show how this phenomenological concept of mood can be smoothly integrated with cognitive neuroscience. We will argue that mood is a consequence of acting in the world with the aim of minimizing expected free energy—a measure of uncertainty about the future consequences of actions. Moods summarize how the organism is faring overall in its predictive engagements, tuning the organism’s expectations about how it is likely to fare in the future. Agents that act to minimize expected free energy will have a feeling of how well or badly they are doing at maintaining grip on the multiple possibilities that matter to them. They will have what we will call a ‘feeling of grip’ that structures the possibilities they are ready to engage with over long time-scales, just as moods do.

scholarly journals “Through others we become ourselves”: The dialectics of predictive coding and active inference

2020 ◽  
Vol 43 ◽  
Author(s):  
Dimitris Bolis ◽  
Leonhard Schilbach
Keyword(s):  
Free Energy ◽  
Social Interaction ◽  
Predictive Coding ◽  
Real Life ◽  
Other Minds ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Multiscale Dynamics ◽  
Cultural Processes

Abstract Thinking through other minds creatively situates the free-energy principle within real-life cultural processes, thereby enriching both sociocultural theories and Bayesian accounts of cognition. Here, shifting the attention from thinking-through to becoming-with, we suggest complementing such an account by focusing on the empirical, computational, and conceptual investigation of the multiscale dynamics of social interaction.

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