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OverviewFull Product DetailsAuthor: Christopher L. Buckley , Daniela Cialfi , Pablo Lanillos , Maxwell RamsteadPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2023 Volume: 1721 Weight: 0.587kg ISBN: 9783031287183ISBN 10: 3031287185 Pages: 372 Publication Date: 22 March 2023 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsPreventing Deterioration of Classification Accuracy in Predictive Coding Networks.- Interpreting systems as solving POMDPs: a step towards a formal understanding of agency.- Disentangling Shape and Pose for Object-Centric Deep Active Inference Models.- Object-based Active Inference.- Knitting a Markov blanket is hard when you are out-of-equilibrium: two examples in canonical nonequilibrium models.- Spin glass systems as collective active inference.- Mapping Husserlian phenomenology onto active inference.- The Role of Valence and Meta-awareness in Mirror Self-recognition Using Hierarchical Active Inference.- World model learning from demonstrations with active inference: application to driving behavior.- Active Blockference: cadCAD with Active Inference for cognitive systems modeling.- Active Inference Successor Representations.- Learning Policies for Continuous Control via Transition Models.- Attachment Theory in an Active Inference Framework: How Does Our Inner Model Take Shape?.- Capsule Networks as Generative Models.- Home run: finding your way home by imagining trajectories.- A Novel Model for Novelty: Modeling the Emergence of Innovation from Cumulative Culture.- Active Inference and Psychology of Expectations: A study of formalizing ViolEx.- AIXI, FEP-AI, and integrated world models: Towards a unified understanding of intelligence and consciousness.- Intention Modulation for Multi-Step Tasks in Continuous Time Active Inference.- Learning Generative Models for Active Inference using Tensor Networks.- A Worked Example of the Bayesian Mechanics of Classical Objects.- A message passing perspective on planning under Active Inference.- Efficient search of active inference policy spaces using k-means.- Value Cores for Inner and Outer Alignment: Simulating Personality Formation via Iterated Policy Selection and Preference Learning with Self-World Modeling Active Inference Agent.- Deriving time-averaged active inference from control principles.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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