Andy Clark (2012) "Whatever Next? Predictive Brains, Situated agents and the future of cognitive science", to appear in Behavioral and Brain Sciences
Here is the download link: http://www.fil.lu.se/files/
Abstract: Brains, it has recently been argued, are
essentially prediction machines. They are bundles of cells that support
perception and action by constantly attempting to match incoming sensory inputs
with top-down expectations or predictions. This is achieved using a
hierarchical generative model that aims to minimize prediction error within a bidirectional
cascade of cortical processing. Such accounts offer a unifying model of perception
and action, illuminate the functional role of attention, and may neatly capture
the special contribution of cortical processing to adaptive success. The paper critically examines this ‘hierarchical prediction
machine’ approach, concluding that it offers the best clue yet to the shape of
a unified science of mind and action. Sections 1 and 2 lay out the
key elements and implications of the approach. Section 3 explores a variety of
pitfalls and challenges, spanning the evidential, the methodological, and the
more properly conceptual. The paper ends (sections 4 and 5) by asking how such
approaches might impact our more general vision of mind, experience, and
agency.
My comment: Although the paper does not involve any computational tools or specific computational frameworks, it in fact points out the incapability of ICA and sparse coding in the computational vision field. Also, I further understand that why deep belief networks and other hierarchical Bayesian models are so promising in the computational vision field.
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