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Associative Learning and Active Inference
Neural ComputationAbstract Associative learning is a behavioral phenomenon in which individuals develop connections between stimuli or events based on their co-occurrence. Initially studied by Pavlov in his conditioning experiments, the fundamental principles of learning have been expanded on through the discovery of a wide range of learning phenomena ...
Anokhin, Petr +3 more
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Active inference and epistemic value
Cognitive Neuroscience, 2015We offer a formal treatment of choice behavior based on the premise that agents minimize the expected free energy of future outcomes. Crucially, the negative free energy or quality of a policy can be decomposed into extrinsic and epistemic (or intrinsic) value.
Friston, K. +5 more
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Meta-learning in active inference
Behavioral and Brain SciencesAbstract Binz et al. propose meta-learning as a promising avenue for modelling human cognition. They provide an in-depth reflection on the advantages of meta-learning over other computational models of cognition, including a sound discussion on how their proposal can accommodate neuroscientific insights.
O. Penacchio, A. Clemente
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Active Inference: The Free Energy Principle in Mind, Brain, and Behaviour
Landscape Journal, 2023D. Jacques
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COGNITIVE INFERENCE IN PERCEPTUAL ACTIVITY
British Journal of Psychology, 1957Whenever sensory data are scanty or ambiguous, or incongruities occur in perceptual situation, observers tend to employ processes of inferential thinking to arrive at satisfactory identifications., Such inferential thinking also appears when observer is called upon to make accurate judgements about events which ordinarily might not be closely observed.
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Active inference and free energy
Behavioral and Brain Sciences, 2013AbstractWhy do brains have so many connections? The principles exposed by Andy Clark provide answers to questions like this by appealing to the notion that brains distil causal regularities in the sensorium and embody them in models of their world. For example, connections embody the fact that causes have particular consequences.
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Generative replay underlies compositional inference in the hippocampal-prefrontal circuit
Cell, 2023Philipp Schwartenbeck
exaly
Causal inference for time series
Nature Reviews Earth & Environment, 2023Jakob Runge, Gherardo Varando
exaly
Interoceptive active inference
Abstract Allostatic active inference is the name for the integrated processing that optimizes organismic function. It derives from the idea that, in order to maintain viability, organisms must implement a model that predicts the consequences of regulatory action. Bodily and affective experiences inform the subject of degree and nature ofopenaire +1 more source