Active Inference First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings

This book constitutes the refereed proceedings of the First International Workshop on Active Inference, IWAI 2020, co-located with ECML/PKDD 2020, held in Ghent, Belgium, in September 2020. The 13 full papers along with 6 short papers were thoroughly reviewed and selected from 25 submissions. They a...

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Main Authors Verbelen, Tim, Lanillos, Pablo, Buckley, Christopher L, De Boom, Cedric
Format eBook Conference Proceeding
LanguageEnglish
Published Cham Springer Nature 2020
Springer International Publishing AG
Springer International Publishing
Edition1
SeriesCommunications in Computer and Information Science
Subjects
Artificial Intelligence
Computer Appl. in Social and Behavioral Sciences
Computer Imaging, Vision, Pattern Recognition and Graphics
Computer Science
Information Systems and Communication Service
Numeric Computing
Numerical analysis-Congresses
Probability and Statistics in Computer Science
Special computer methods
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Abstract This book constitutes the refereed proceedings of the First International Workshop on Active Inference, IWAI 2020, co-located with ECML/PKDD 2020, held in Ghent, Belgium, in September 2020. The 13 full papers along with 6 short papers were thoroughly reviewed and selected from 25 submissions. They are organized in the topical sections on active inference and continuous control; active inference and machine learning; active inference: theory and biology.
AbstractList This book constitutes the refereed proceedings of the First International Workshop on Active Inference, IWAI 2020, co-located with ECML/PKDD 2020, held in Ghent, Belgium, in September 2020. The 13 full papers along with 6 short papers were thoroughly reviewed and selected from 25 submissions. They are organized in the topical sections on active inference and continuous control; active inference and machine learning; active inference: theory and biology.
Author Verbelen, Tim
De Boom, Cedric
Buckley, Christopher L
Lanillos, Pablo
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Snippet This book constitutes the refereed proceedings of the First International Workshop on Active Inference, IWAI 2020, co-located with ECML/PKDD 2020, held in...
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SubjectTerms Artificial Intelligence
Computer Appl. in Social and Behavioral Sciences
Computer Imaging, Vision, Pattern Recognition and Graphics
Computer Science
Information Systems and Communication Service
Numeric Computing
Numerical analysis-Congresses
Probability and Statistics in Computer Science
Special computer methods
Subtitle First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings
TableOfContents 3 Results -- 4 Conclusions -- References -- Learning Where to Park -- 1 Introduction -- 2 Problem Statement -- 3 Model Specification -- 3.1 The Physical Model -- 3.2 The Target Model -- 4 Experimental Validation -- 4.1 Setup -- 4.2 Results -- 5 Related Work -- 6 Conclusions -- References -- Active Inference: Theory and Biology -- Integrated World Modeling Theory (IWMT) Implemented: Towards Reverse Engineering Consciousness with the Free Energy Principle and Active Inference -- 1 Integrated World Modeling Theory (IWMT) Summarized: Combining the Free Energy Principle and Active Inference (FEP-AI) Framework with Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNWT) -- 2 Integrated World Modeling Theory (IWMT) Implemented -- 2.1 Mechanisms of Predictive Processing: Folded Variational Autoencoders (VAEs) and Self-organizing Harmonic Modes (SOHMs) -- 2.2 A Model of Episodic Memory and Imagination -- 2.3 Brains as Hybrid Machine Learning Architectures -- 2.4 Conclusion: Functions of Basic Phenomenal Consciousness? -- 3 Appendices -- 3.1 Appendix 1: A Model of Goal-Oriented Behavior with Hippocampal Orchestration -- 3.2 Appendix 2: The VAE-GAN Brain? -- References -- Confirmatory Evidence that Healthy Individuals Can Adaptively Adjust Prior Expectations and Interoceptive Precision Estimates -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Visual Search as Active Inference -- 1 Introduction -- 2 Problem Statement: Formalizing Visual Search as Accuracy Seeking -- 2.1 Visual Search Task -- 2.2 Central Processing -- 2.3 Accuracy Map -- 3 Principles: Supervised Learning of Action Selection -- 3.1 Peripheral Visual Processing -- 3.2 Motor Control -- 3.3 Higher Level Inference: Choosing the Processing Pathway -- 3.4 Learning the Accuracy Map -- 4 Results -- 5 Discussion and Perspectives -- References
Sophisticated Affective Inference: Simulating Anticipatory Affective Dynamics of Imagining Future Events -- 1 Introduction -- 2 Methods -- 3 Results -- References -- Causal Blankets: Theory and Algorithmic Framework -- 1 Introduction -- 1.1 Markov Blankets -- 1.2 Computational Mechanics, Causal States, and Epsilon-Machines -- 1.3 Contribution -- 2 Causal Blankets as Informational Boundaries -- 3 Integrated Information Transcends the Blankets -- 4 Conclusion -- A Proofs -- References -- Author Index
Intro -- Preface -- Organization -- Contents -- Active Inference and Continuous Control -- On the Relationship Between Active Inference and Control as Inference -- 1 Introduction -- 2 Formalism -- 3 Control as Inference -- 4 Active Inference -- 5 Encoding Value -- 6 Discussion -- References -- Active Inference or Control as Inference? A Unifying View -- 1 Introduction -- 2 Background -- 2.1 Problem Formulation -- 2.2 Variational Inference for Latent Variable Models -- 3 Active Inference -- 3.1 Free Energy of the Future -- 3.2 Active Inference in Practice -- 4 Control as Inference -- 4.1 Linear Gaussian Inference and Linear Quadratic Control -- 5 The Unifying View: Control of the Observations -- 6 Conclusion -- References -- Active Inference for Fault Tolerant Control of Robot Manipulators with Sensory Faults -- 1 Introduction -- 2 Problem Statement -- 3 A Fault Tolerant Scheme Based on Active Inference -- 4 Simulation Results -- 5 Discussion and Conclusion -- References -- A Worked Example of Fokker-Planck-Based Active Inference -- 1 Introduction -- 2 The Fokker-Planck Equation for Dynamical Systems -- 3 Laplace-Encoded Free Energy and Generative Models -- 4 A Worked Example -- 5 Results -- 6 Discussion -- References -- Dynamics of a Bayesian Hyperparameter in a Markov Chain -- 1 Introduction -- 2 IID Parameter Inference -- 2.1 Fully Observable Markov Chain -- References -- Online System Identification in a Duffing Oscillator by Free Energy Minimisation -- 1 Introduction -- 2 System -- 3 Identification -- 3.1 Free Energy Minimisation -- 3.2 Factor Graphs and Message Passing -- 4 Experiment -- 4.1 1-Step Ahead Prediction Error -- 4.2 Simulation Error -- 5 Discussion -- 5.1 Related Work -- 6 Conclusion -- References -- Hierarchical Gaussian Filtering of Sufficient Statistic Time Series for Active Inference -- 1 Introduction
2 Bayesian Inference Reduced to Mean-Tracking -- 2.1 Mean Tracking and Exponential Weighting -- 2.2 A Conjugate Prior Which Reduces Bayesian Inference to Mean Tracking for Exponential Families -- 3 Predictive Distributions -- 4 Filtering of Sufficient Statistics for Non-stationary Input Distributions -- 5 Discussion -- References -- Active Inference and Machine Learning -- Deep Active Inference for Partially Observable MDPs -- 1 Introduction -- 2 Deep Active Inference Model -- 3 Experimental Setup -- 4 Results -- 5 Conclusion -- References -- Sleep: Model Reduction in Deep Active Inference -- 1 Introduction -- 2 Deep Active Inference -- 3 Latent Space Dimensionality Reduction and Sleep -- 4 Experimental Setup -- 5 Results -- 6 Conclusion -- References -- A Deep Active Inference Model of the Rubber-Hand Illusion -- 1 Introduction -- 2 Deep Active Inference Model -- 2.1 Generative Model Learning -- 2.2 Modelling Visuo-Tactile Stimulation Synchrony -- 3 Experimental Setup -- 4 Results -- 5 Conclusion -- References -- You Only Look as Much as You Have To -- 1 Introduction -- 2 Active Inference -- 3 Environment and Approach -- 4 Experiments -- 4.1 Exploring Behaviour -- 4.2 Goal Seeking Behaviour -- 5 Conclusion -- A The Generative Model -- References -- Modulation of Viability Signals for Self-regulatory Control -- 1 Introduction -- 2 Preliminaries -- 2.1 Model-Free Surprisal Minimization -- 2.2 Expected Free Energy -- 3 Adaptive Control via Self-regulation -- 3.1 Case Study -- 3.2 Evaluation -- 4 Discussion -- A Expected Free Energy with Measurements v -- B Novelty and salience -- C Implementation -- D Drive decomposition -- References -- End-Effect Exploration Drive for Effective Motor Learning -- 1 Introduction -- 2 Method -- 2.1 A Probabilistic View to Motor Supervision -- 2.2 A Uniform Exploration Drive -- 2.3 Link with Variational Inference
Title Active Inference
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