Results 41 to 50 of about 649,550 (269)
Biological Cybernetics, 2018 This work combines the free energy principle from cognitive neuroscience and the ensuing active inference dynamics with recent advances in variational inference in deep generative models, and evolution strategies to introduce the "deep active inference" agent.
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Active inference, evidence accumulation, and the urn task [PDF]
, 2015 Deciding how much evidence to accumulate before making a decision is a problem we and other animals often face, but one that is not completely understood.
Attias H. +7 more
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Flexible intentions: An Active Inference theory
Frontiers in Computational Neuroscience, 2023 We present a normative computational theory of how the brain may support visually-guided goal-directed actions in dynamically changing environments. It extends the Active Inference theory of cortical processing according to which the brain maintains ...
Matteo Priorelli, Ivilin Peev Stoianov
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The cybernetic Bayesian brain: from interoceptive inference to sensorimotor contingencies [PDF]
, 2015 Is there a single principle by which neural operations can account for perception, cognition, action, and even consciousness? A strong candidate is now taking shape in the form of “predictive processing”.
Seth, Anil K
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, 2023 The world consists of objects: distinct entities possessing independent properties and dynamics. For agents to interact with the world intelligently, they must translate sensory inputs into the bound-together features that describe each object. These object-based representations form a natural basis for planning behavior.
Ruben S. van Bergen, Pablo Lanillos
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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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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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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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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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