Special Issue "Emerging Methods in Active Inference"
Deadline for manuscript submissions: 11 July 2022 | Viewed by 4739
Interests: active inference; Bayesian mechanics; theoretical neurobiology; computational neurology
Interests: active inference; sensorimotor control; action–perception loop; control theory; filtering theory; dynamical systems; cognitive computational neuroscience; artificial life
Interests: active inference; variational methods; message passing; probabilistic programming
2. Department of General Psychiatry, Centre of Psychosocial Medicine, Heidelberg University Hospital, Voßstraße 2, 69115 Heidelberg, Germany
Interests: computational biology; theoretical neurobiology; deep generative models; stochastic thermodynamics; approximate Bayesian inference
Special Issues, Collections and Topics in MDPI journals
Active inference is a formal approach for characterizing behavior. Although originally developed in theoretical neurobiology, it has found a diverse range of applications—from morphogenesis to robotics. Over the last few years, this range of applications has been matched with novel implementations of active inference. These vary along several dimensions. They exist for discrete or continuous time, as well as for continuous or categorical variables. Some versions use factor-graph-based message passing and variational inference, employing mean field or Bethe approximations. Others use Monte Carlo sampling schemes. Some focus on the underlying physics and Fokker–Planck formalisms. Others exploit technologies developed in deep learning and machine learning—such as the variational autoencoder—to facilitate application to large scale problems. This Special Issue aims to showcase the emerging spectrum of methods for active inference, as well as the kinds of questions they are designed to address.
Dr. Thomas Parr
Dr. Manuel Baltieri
Dr. Thijs van de Laar
Dr. Kai Ueltzhöffer
Dr. Daniela Cialfi
Prof. Dr. Karl Friston
Ms. Noor Sajid
Assistant Guest Editor
Affiliation: The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
Interests: active (variational) inference; degeneracy; adaptation
Manuscript Submission Information
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- active inference