scholarly journals Resonating Minds—Emergent Collaboration Through Hierarchical Active Inference

2021 ◽  
Author(s):  
Jan Pöppel ◽  
Sebastian Kahl ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Predictive Processing ◽  
Active Inference ◽  
Collaborative Reasoning ◽  
Computational Costs ◽  
Task Behavior ◽  
Working Together ◽  
Actual Interaction ◽  
Agent Coordination ◽  
Perception Action

AbstractWorking together on complex collaborative tasks requires agents to coordinate their actions. Doing this explicitly or completely prior to the actual interaction is not always possible nor sufficient. Agents also need to continuously understand the current actions of others and quickly adapt their own behavior appropriately. Here we investigate how efficient, automatic coordination processes at the level of mental states (intentions, goals), which we call belief resonance, can lead to collaborative situated problem-solving. We present a model of hierarchical active inference for collaborative agents (HAICA). It combines efficient Bayesian Theory of Mind processes with a perception–action system based on predictive processing and active inference. Belief resonance is realized by letting the inferred mental states of one agent influence another agent’s predictive beliefs about its own goals and intentions. This way, the inferred mental states influence the agent’s own task behavior without explicit collaborative reasoning. We implement and evaluate this model in the Overcooked domain, in which two agents with varying degrees of belief resonance team up to fulfill meal orders. Our results demonstrate that agents based on HAICA achieve a team performance comparable to recent state-of-the-art approaches, while incurring much lower computational costs. We also show that belief resonance is especially beneficial in settings where the agents have asymmetric knowledge about the environment. The results indicate that belief resonance and active inference allow for quick and efficient agent coordination and thus can serve as a building block for collaborative cognitive agents.

scholarly journals A predictive processing theory of motivation

Synthese ◽  
2019 ◽  
Author(s):  
Alex James Miller Tate
Keyword(s):  
Characteristic Function ◽  
Control Function ◽  
Mental States ◽  
Predictive Processing ◽  
Active Inference ◽  
Contemporary Debate ◽  
Processing Theory ◽  
Significant Step ◽  
Argument Proceeds ◽  
Predictive Theory

Abstract In this paper I propose minimal criteria for a successful theory of the mechanisms of motivation (i.e. how motivational mental states perform their characteristic function), and argue that extant philosophical accounts fail to meet them. Further, I argue that a predictive processing (PP) framework gives us the theoretical power to meet these criteria, and thus ought to be preferred over existing theories. The argument proceeds as follows—motivational mental states are generally understood as mental states with the power to initiate, guide, and control action, though few existing theories of motivation explicitly detail how they are meant to explain these functions. I survey two contemporary theories of motivational mental states, due to Wayne Wu and Bence Nanay, and argue that they fail to satisfactorily explain one or more of these functions. Nevertheless, I argue that together, they are capable of giving a strong account of the control function, which competing theories ought to preserve (all else being equal). I then go on to argue that what I call the ‘predictive theory’ of motivational mental states, which makes use of the notion of active inference, is able to explain all three of the key functions and preserves the central insights of Wu and Nanay on control. It thus represents a significant step forward in the contemporary debate.

Activity, Agency, and Inner Speech Pathology

2018 ◽  
Author(s):  
Lauren Swiney
Keyword(s):  
Motor Control ◽  
Sensory Input ◽  
The Other ◽  
Predictive Processing ◽  
Inner Speech ◽  
Speech Pathology ◽  
Active Inference ◽  
Comparator Hypothesis

Over the last thirty years the comparator hypothesis has emerged as a prominent account of inner speech pathology. This chapter discusses a number of cognitive accounts broadly derived from this approach, highlighting the existence of two importantly distinct notions of inner speech in the literature; one as a prediction in the absence of sensory input, the other as an act with sensory consequences that are themselves predicted. Under earlier frameworks in which inner speech is described in the context of classic models of motor control, I argue that these two notions may be compatible, providing two routes to inner speech pathology. Under more recent accounts grounded in the architecture of Bayesian predictive processing, I argue that “active inference” approaches to action generation pose serious challenges to the plausibility of the latter notion of inner speech, while providing the former notion with rich explanatory possibilities for inner speech pathology.

scholarly journals Implementing Predictive Processing and Active Inference: Preliminary Steps and Results

2019 ◽  
Author(s):  
Beren Millidge
Keyword(s):  
Predictive Coding ◽  
Predictive Processing ◽  
Active Inference ◽  
Inference Models ◽  
Perceptual Model ◽  
Challenging Tasks ◽  
Generalised Coordinates

Initial and preliminary implementations of predictive processing and active inference models are presented. These include the baseline hierarchical predictive coding models of (Friston 2003, 2005), and dynamical predictive coding models using generalised coordinates (Friston 2008, 2010, Buckley 2017). Additionally, we re-implement and experiment with the active inference thermostat presented in (Buckley 2017) and also implement an active inference agent with a hierarchical predictive coding perceptual model on the more challenging cart-pole task from OpanAI gym. We discuss the initial performance, capabilities, and limitations of these models in their preliminary stages and consider how they might be further scaled up to tackle more challenging tasks.

Embodiment in Religious Knowledge

2005 ◽  
Vol 5 (1-2) ◽  
pp. 14-57 ◽  
Author(s):  
Aron Barbey ◽  
Lawrence Barsalou ◽  
W. Kyle Simmons ◽  
Ava Santos
Keyword(s):  
Cognitive Neuroscience ◽  
Religious Beliefs ◽  
Mental States ◽  
The Body ◽  
Religious Knowledge ◽  
Daily Experience ◽  
Religious Rituals ◽  
Actual Experience ◽  
Perception Action ◽  
Representation Of Knowledge

AbstractIncreasing evidence suggests that mundane knowledge about objects, people, and events is grounded in the brain's modality-specific systems. The modality-specific representations that become active to represent these entities in actual experience are later used to simulate them in their absence. In particular, simulations of perception, action, and mental states often appear to underlie the representation of knowledge, making it embodied and situated. Findings that support this conclusion are briefly reviewed from cognitive psychology, social psychology, and cognitive neuroscience. A similar representational process may underlie religious knowledge. In support of this conjecture, embodied knowledge appears central to three aspects of religious experience: religious visions, religious beliefs, and religious rituals. In religious visions, the process of simulation offers a natural account of how these experiences are produced. In religious beliefs, knowledge about the body and the environment are typically central in religious frameworks, and are likely to affect the perception of daily experience. In religious rituals, embodiments appear central to conveying religious ideas metaphorically and to establishing them in memory. To the extent that religious knowledge is like non-religious knowledge, embodiment is likely to play central roles.

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 Neuronal cell-type and circuit basis for visual predictive processing

2022 ◽  
Author(s):  
Jinmao Zou ◽  
Lawrence Huang ◽  
Lizhao Wang ◽  
Yuanyuan Xu ◽  
Chenchang Li ◽  
...  
Keyword(s):  
Neural Circuit ◽  
Neuronal Cell ◽  
Predictive Processing ◽  
Psychiatric Disease ◽  
Inhibitory Interneurons ◽  
Cell Type ◽  
Bayesian Brain ◽  
Action And Perception ◽  
Brain Theory ◽  
Perception Action

Bayesian Brain theory suggests brain utilises predictive processing framework to interpret the noisy world. Predictive processing is essential to perception, action, cognition and psychiatric disease, but underlying neural circuit mechanisms remain undelineated. Here we show the neuronal cell-type and circuit basis for visual predictive processing in awake, head-fixed mice during self-initiated running. Preceding running, vasoactive intestinal peptide (VIP)-expressing inhibitory interneurons (INs) in primary visual cortex (V1) are robustly activated in absence of structured visual stimuli. This pre-running activation is mediated via distal top-down projections from frontal, parietal and retrosplenial areas known for motion planning, but not local excitatory inputs associated with the bottom-up pathway. Somatostatin (SST) INs show pre-running suppression and post-running activation, indicating a VIP-SST motif. Differential VIP-SST peri-running dynamics anisotropically suppress neighbouring pyramidal (Pyr) neurons, preadapting Pyr neurons to the incoming running. Our data delineate key neuron types and circuit elements of predictive processing brain employs in action and perception.

scholarly journals The Acquisition of Culturally Patterned Attention Styles Under Active Inference

2021 ◽  
Vol 15 ◽  
Author(s):  
Axel Constant ◽  
Alexander Daniel Dunsmoir Tschantz ◽  
Beren Millidge ◽  
Felipe Criado-Boado ◽  
Luis M Martinez ◽  
...  
Keyword(s):  
Material Culture ◽  
Task Performance ◽  
Visual Discrimination ◽  
Discrimination Task ◽  
Cognitive Task ◽  
Active Inference ◽  
Human Thought ◽  
Cognitive Task Performance ◽  
Future Work ◽  
Perception Action

This paper presents an active inference based simulation study of visual foraging. The goal of the simulation is to show the effect of the acquisition of culturally patterned attention styles on cognitive task performance, under active inference. We show how cultural artefacts like antique vase decorations drive cognitive functions such as perception, action and learning, as well as task performance in a simple visual discrimination task. We thus describe a new active inference based research pipeline that future work may employ to inquire on deep guiding principles determining the manner in which material culture drives human thought, by building and rebuilding our patterns of attention.

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 Perceptual justification in the Bayesian brain: a foundherentist account

Synthese ◽  
2021 ◽  
Author(s):  
Paweł Gładziejewski
Keyword(s):  
Mental States ◽  
Predictive Processing ◽  
Perceptual Justification ◽  
Bayesian Brain ◽  
The Mind ◽  
Epistemology Of Perception

AbstractIn this paper, I use the predictive processing (PP) theory of perception to tackle the question of how perceptual states can be rationally involved in cognition by justifying other mental states. I put forward two claims regarding the epistemological implications of PP. First, perceptual states can confer justification on other mental states because the perceptual states are themselves rationally acquired. Second, despite being inferentially justified rather than epistemically basic, perceptual states can still be epistemically responsive to the mind-independent world. My main goal is to elucidate the epistemology of perception already implicit in PP. But I also hope to show how it is possible to peacefully combine central tenets of foundationalist and coherentist accounts of the rational powers of perception while avoiding the well-recognized pitfalls of either.

scholarly journals Out of the blue: understanding abrupt and wayward transitions in thought using probability and predictive processing

2020 ◽  
Vol 376 (1817) ◽  
pp. 20190692
Author(s):  
Caitlin Mills ◽  
Andre Zamani ◽  
Rebecca White ◽  
Kalina Christoff
Keyword(s):  
Mental States ◽  
Predictive Processing ◽  
Theme Issue ◽  
Probability Metrics ◽  
External Stimulation ◽  
Novel Approach ◽  
Mental Experience ◽  
Neural Processes ◽  
Different Types ◽  
To Come

Thoughts that appear to come to us ‘out of the blue’ or ‘out of nowhere’ are a familiar aspect of mental experience. Such thoughts tend to elicit feelings of surprise and spontaneity. Although we are beginning to understand the neural processes that underlie the arising of such thoughts, little is known about what accounts for their peculiar phenomenology. Here, we focus on one central aspect of this phenomenology—the experience of surprise at their occurrence, as it relates to internal probabilistic predictions regarding mental states. We introduce a distinction between two phenomenologically different types of transitions in thought content: (i) abrupt transitions , which occur at surprising times but lead to unsurprising thought content, and (ii) wayward transitions , which occur at surprising times and also lead to surprising thought content. We examine these two types of transitions using a novel approach that combines probabilistic and predictive processing concepts and principles. We employ two different probability metrics—transition and occurrence probability—to characterize and differentiate between abrupt and wayward transitions. We close by discussing some potentially beneficial ways in which these two kinds of transitions in thought content may contribute to mental function, and how they may be implemented at the neural level. This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.

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