Results 51 to 60 of about 3,880,038 (272)
Active Inference, Curiosity and Insight [PDF]
Neural Computation, 2017 This article offers a formal account of curiosity and insight in terms of active (Bayesian) inference. It deals with the dual problem of inferring states of the world and learning its statistical structure. In contrast to current trends in machine learning (e.g., deep learning), we focus on how people attain insight and understanding using just a ...
Karl J. Friston +5 more
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CoRR, 2018 We describe a framework of hybrid cognition by formulating a hybrid cognitive agent that performs hierarchical active inference across a human and a machine part. We suggest that, in addition to enhancing human cognitive functions with an intelligent and adaptive interface, integrated cognitive processing could accelerate emergent properties within ...
André Ofner, Sebastian Stober
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A Variational Synthesis of Evolutionary and Developmental Dynamics
Entropy, 2023 This paper introduces a variational formulation of natural selection, paying special attention to the nature of ‘things’ and the way that different ‘kinds’ of ‘things’ are individuated from—and influence—each other.
Karl Friston +6 more
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Active inference and agency [PDF]
Cognitive Neuroscience, 2014 I greatly enjoyed Seth's compelling synthesis of sensorimotor contingencies and active inference. I would also like to thank Jim Hopkins for sending me the quote (below)-which speaks directly to the embodied nature of perceptual inference that underlies the perspectives reconciled in Seth (this issue).
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Enactive-Dynamic Social Cognition and Active Inference
Frontiers in Psychology, 2022 This aim of this paper is two-fold: it critically analyses and rejects accounts blending active inference as theory of mind and enactivism; and it advances an enactivist-dynamic understanding of social cognition that is compatible with active inference ...
Inês Hipólito +2 more
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Deconstructing Deep Active Inference
, 2023 Active inference is a theory of perception, learning and decision making, which can be applied to neuroscience, robotics, and machine learning. Recently, reasearch has been taking place to scale up this framework using Monte-Carlo tree search and deep learning.
Théophile Champion +3 more
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Active Inference and Learning in the Cerebellum [PDF]
Neural Computation, 2016 This letter offers a computational account of Pavlovian conditioning in the cerebellum based on active inference and predictive coding. Using eyeblink conditioning as a canonical paradigm, we formulate a minimal generative model that can account for spontaneous blinking, startle responses, and (delay or trace) conditioning.
Karl J. Friston, Ivan Herreros-Alonso
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Visual Search as Active Inference [PDF]
, 2020 Visual search is an essential cognitive ability, offering a prototypical control problem to be addressed with Active Inference. Under a Naive Bayes assumption, the maximization of the information gain objective is consistent with the separation of the visual sensory flow in two independent pathways, namely the “What” and the “Where” pathways.
Daucé, Emmanuel, Perrinet, Laurent U
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Deep Active Inference and Scene Construction
Frontiers in Artificial Intelligence, 2020 Adaptive agents must act in intrinsically uncertain environments with complex latent structure. Here, we elaborate a model of visual foraging—in a hierarchical context—wherein agents infer a higher-order visual pattern (a “scene”) by sequentially ...
R. Conor Heins +11 more
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Canonical neural networks perform active inference
Communications Biology, 2022 Takuya Isomura, Hideaki Shimazaki and Karl Friston perform mathematical analysis to show that neural networks implicitly perform active inference and learning to minimise the risk associated with future outcomes.
Takuya Isomura +2 more
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