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The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior-a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a "first principles" approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.
Thomas Parr is a Postdoctoral Scholar at the Wellcome Centre for Human Neuroimaging at the Queen Square Institute of Neurology at University College London and a practicing clinician. Giovanni Pezzulo is a Researcher at the Institute of Cognitive Sciences and Technologies of the National Research Council of Italy in Rome. Karl J. Friston is Scientific Director of the Wellcome Centre for Human Neuroimaging and Professor at Queen Square Institute of Neurology at University College London.
Preface vii I 1 Overview 3 2 The Low Road to Active Inference 15 3 The High Road to Active Inference 41 4 The Generative Models of Active Inference 63 5 Message Passing and Neurobiology 85 II 6 A Recipe for Designing Active Inference Models 105 7 Active Inference in Discrete Time 125 8 Active Inference in Continuous Time 153 9 Model-Based Data Analysis 173 10 Active Inference as a Unified Theory of Sentient Behavior 191 Appendix A: Mathematical Background 225 Appendix B: The Equations of Active Inference 243 Appendix C: An Annotated Example of the Matlab Code 259 Notes 267 References 273 Index 295
