Prof. Karl Friston (London, UK)

A Free energy principle for the brain
Value-learning and perceptual learning have been an important focus over the past decade, attracting the concerted attention of experimental psychologists, neurobiologists and the machine learning community. Despite some formal connections; e.g., the role of prediction error in optimizing some function of sensory states, both fields have developed their own rhetoric and postulates. In work, we show that perceptual learning is, literally, an integral part of value learning; in the sense that perception is necessary to integrate out dependencies on the inferred causes of sensory information. This enables the value of sensory trajectories to be optimized through action. Furthermore, we show that acting to optimize value and perception are two aspects of exactly the same principle; namely the minimization of a quantity [free energy] that bounds the probability of sensory input, given a particular agent or phenotype. This principle can be derived, in a straightforward way, from the very existence of agents, by considering the probabilistic behavior of an ensemble of agents belonging to the same class.

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25.02.2009/cb