Surfing Uncertainty: Prediction, Action, and the Embodied Mind

By Andy Clark. 2015

491 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9ddfcd5a252f2323ac783d07368b63fcccad663e

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Citations in the corpus

How to Knit Your Own Markov Blanket (2017, background): “Attentional mechanisms, that story suggests, alter patterns of inner (neural) effective connectivity so as to enforce information flows that are highly specialized for the task at hand (Clark 2016, Clark in press).”
Predictive Processing: A Canonical Cortical Computation (2018, methodology): “Given our frequent disagreements with others over the attributes of objects we see, or over what we hear, it is probably appropriate to describe perception as a controlled hallucination (Clark, 2016).”
REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics (2019, background): “, precise) prediction errors, manifesting as aberrant salience (Kapur, 2003) in the early phase of a psychosis, followed by the formation of heavily weighted and therefore stabilizing, but delusional high-level priors, has been discussed before (Clark, 2016).”
Hierarchical Active Inference: A Theory of Motivated Control (2018, background): “Within active inference, motivated control operates to reducing exteroceptive, interoceptive and proprioceptive prediction errors, at all hierarchical levels [15,66 – 69].”
A nice surprise? Predictive processing and the active pursuit of novelty (2018, background): “But as a kind of spin-off from all this deep (and language-enriched – see (Lupyan and Clark 2015)) model-building activity, we humans also began to construct complex social and physical environments.”
6G Networks: Beyond Shannon Towards Semantic and Goal-Oriented Communications (2020, background): “…theory denoted as predictive mind , supported by experimental evidence, that our mind works as a predictive machine that continuously predicts what is going to experience from its senses and updates its (hierarchical) interpretation models accordingly, learning from prediction errors [39], [40].”
Action Is Enabled by Systematic Misrepresentations (2017, methodology): “The framework of predictive processing (PP) depicts neural activity as a hierarchically distributed process of minimizing precision-weighted prediction error (cf. Clark, 2013, 2016; Hohwy, 2013).”
Busting Out: Predictive Brains, Embodied Minds, and the Puzzle of the Evidentiary Veil (2017, background): “Instead, the role of the inner model is, in very many daily settings, to spot help spot the contexts in which some more frugal, actiondependent, procedure will work (we return to this hybrid picture in sections 7-9 below – see also Clark (2016)).”
Real Virtuality: A Code of Ethical Conduct. Recommendations for Good Scientific Practice and the Consumers of VR-Technology (2016, background): “…mind and conscious experience itself describe it in a very similar way: leading current theories of brain dynamics (Friston, 2010; Hohwy, 2013; Clark, 2015) describe it as the constant creation of internal models of the world, predictively generating hypotheses – virtual neural…”