This volume constitutes the papers of the 3rd International Workshop on Active Inference, IWAI 2022, held in Grenoble, France, in conjunction with ECML/PKDD, on September 19, 2022.
The 25 revised full papers presented in this book were carefully reviewed and selected from 31 submissions.

Inhalt
Preventing 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 anActive 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.