Fundamentals of Active Inference. Principles, Algorithms, and Applications of the Free Energy Principle for Engineers
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- Nombre de pages576
- FormatePub
- ISBN978-0-262-38514-5
- EAN9780262385145
- Date de parution17/03/2026
- Protection num.Adobe DRM
- Taille38 Mo
- Infos supplémentairesepub
- ÉditeurThe MIT Press
Résumé
A comprehensive, up-to-date introduction to active inference and the free energy principle for an engineering-focused audience. This textbook provides comprehensive coverage of the foundational material needed to understand the interdisciplinary, fast-moving field of active inference from first principles. Using a simple, conversational style free of proofs, lemmas, and theorems, Sanjeev Namjoshi brings together theory and technical material in one self-contained text.
The book first explains the general statistical framework used in active inference models and then introduces fundamental concepts in machine learning and statistics, connecting them to the active inference perspective. Featuring worked examples, simulations, and detailed walk-throughs of concepts, this user-friendly text aims to expand the readership of active inference to an engineering-focused audience.
Provides a one-stop-shop for understanding the foundations and applications of active inference and the free energy principle Makes a complex, interdisciplinary subject accessible to students and professionals beyond the neurosciences Covers discrete and continuous state-space formulations of active inference as well as state-of-the-art extensions to base active inference methods Features extensive appendices and supplemental resources
The book first explains the general statistical framework used in active inference models and then introduces fundamental concepts in machine learning and statistics, connecting them to the active inference perspective. Featuring worked examples, simulations, and detailed walk-throughs of concepts, this user-friendly text aims to expand the readership of active inference to an engineering-focused audience.
Provides a one-stop-shop for understanding the foundations and applications of active inference and the free energy principle Makes a complex, interdisciplinary subject accessible to students and professionals beyond the neurosciences Covers discrete and continuous state-space formulations of active inference as well as state-of-the-art extensions to base active inference methods Features extensive appendices and supplemental resources