Active inference models do not contradict folk psychology

Synthese, Journal Year: 2022, Volume and Issue: 200(2)

Published: March 9, 2022

Abstract Active inference offers a unified theory of perception, learning, and decision-making at computational neural levels description. In this article, we address the worry that active may be in tension with belief–desire–intention (BDI) model within folk psychology because it does not include terms for desires (or other conative constructs) mathematical level To resolve concern, first provide brief review historical progression from predictive coding to inference, enabling us distinguish between formulations motor control (which need have under psychology) decision processes do psychology). We then show that, despite superficial when viewed description, formalism contains are readily identifiable as encoding both objects desire strength psychological demonstrate simple simulations an agent motivated leave dark room different reasons. Despite their consistency, further how increase granularity folk-psychological descriptions by highlighting distinctions drives seek information versus reward—and also offer more precise, quantitative predictions. Finally, consider implicitly components partial analogues (i.e., “as if” desires) systems describable broader free energy principle which conforms.

Language: Английский

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How Active Inference Could Help Revolutionise Robotics

Entropy, Journal Year: 2022, Volume and Issue: 24(3), P. 361 - 361

Published: March 2, 2022

Recent advances in neuroscience have characterised brain function using mathematical formalisms and first principles that may be usefully applied elsewhere. In this paper, we explain how active inference—a well-known description of sentient behaviour from neuroscience—can exploited robotics. short, inference leverages the processes thought to underwrite human build effective autonomous systems. These systems show state-of-the-art performance several robotics settings; highlight these framework used advance

Language: Английский

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Active inference unifies intentional and conflict-resolution imperatives of motor control

PLoS Computational Biology, Journal Year: 2022, Volume and Issue: 18(6), P. e1010095 - e1010095

Published: June 17, 2022

The field of motor control has long focused on the achievement external goals through action (e.g., reaching and grasping objects). However, recent studies in conditions multisensory conflict, such as when a subject experiences rubber hand illusion or embodies an avatar virtual reality, reveal presence unconscious movements that are not goal-directed, but rather aim at resolving conflicts; for example, by aligning position person’s arm with embodied avatar. This second, conflict-resolution imperative movement did emerge classical adaptation online corrections, which allow to reduce been largely ignored so far formal theories. Here, we propose model grounded theory active inference integrates intentional imperatives. We present three simulations showing is able characterize guided intention achieve goal, necessity resolve both. Furthermore, our fundamental difference between (active) underlying imperatives it driven two different (model sensory) kinds prediction errors. Finally, show only conflict resolution, incorrectly infers velocity zero, if was moving. result suggests novel speculative explanation fact people unaware their subtle compensatory avoid conflict. can potentially help shed light deficits awareness arise psychopathological conditions.

Language: Английский

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Slower Learning Rates from Negative Outcomes in Substance Use Disorder over a 1-Year Period and Their Potential Predictive Utility

Computational Psychiatry, Journal Year: 2022, Volume and Issue: 6(1), P. 117 - 117

Published: June 8, 2022

Computational modelling is a promising approach to parse dysfunctional cognitive processes in substance use disorders (SUDs), but it unclear how much these change during the recovery period. We assessed 1-year follow-up data on sample of treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, hallucinogens, and/or opioids; N = 83) that were previously at baseline within prior computational study. Relative healthy controls (HCs; 48), participants found show altered learning rates and less precise action selection while completing an explore-exploit decision-making task. Here we replicated analyses when returned re-performed task 1 year later assess stability differences. also examined whether measures could predict symptoms follow-up. Bayesian frequentist indicated that: (a) group differences stable over time (posterior probability 1); (b) intra-class correlations (ICCs) between model parameters significant ranged from small moderate (.25 ≤ ICCs .54). Exploratory suggested information-seeking values associated severity stimulant opioid users (.36 rs .43). These findings suggest dysfunctions are moderately correspond trait-like vulnerability factors. In addition, had some predictive value for changes be clinically informative.

Language: Английский

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Hierarchical predictive coding in distributed pain circuits

Frontiers in Neural Circuits, Journal Year: 2023, Volume and Issue: 17

Published: March 3, 2023

Predictive coding is a computational theory on describing how the brain perceives and acts, which has been widely adopted in sensory processing motor control. Nociceptive pain involves large distributed network of circuits. However, it still unknown whether this completely decentralized or requires networkwide coordination. Multiple lines evidence from human animal studies have suggested that cingulate cortex insula (cingulate-insula network) are two major hubs mediating information afferents spinothalamic inputs, whereas subregions cortices distinct projections functional roles. In mini-review, we propose an updated hierarchical predictive framework for perception discuss its related computational, algorithmic, implementation issues. We suggest active inference as generalized algorithm, hierarchically organized traveling waves independent neural oscillations plausible mechanism to integrate bottom-up top-down across

Language: Английский

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