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Special Issue "Emerging Methods in Active Inference"
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".
Deadline for manuscript submissions: closed (11 July 2022) | Viewed by 10868
Special Issue Editors
E-Mail Website1 Website2
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
grade E-Mail Website
Interests: theoretical neurobiology; computational neuroscience; neuroimaging; schizophrenia
Special Issue Information
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
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- active inference