Active Inference: 5th International Workshop, IWAI 2024, Oxford, UK, September 9–11, 2024, Revised Selected Papers

Author:   Christopher L. Buckley ,  Daniela Cialfi ,  Pablo Lanillos ,  Riddhi J. Pitliya
Publisher:   Springer International Publishing AG
Volume:   2193
ISBN:  

9783031771378


Pages:   290
Publication Date:   13 December 2024
Format:   Paperback
Availability:   Not yet available   Availability explained
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Active Inference: 5th International Workshop, IWAI 2024, Oxford, UK, September 9–11, 2024, Revised Selected Papers


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Overview

This book constitutes the revised selected papers of the 5th International Workshop on Active Inference, IWAI 2024, held in Oxford, UK, during September 9–11, 2024. The 17 full papers included in this book were carefully reviewed and selected from 54 submissions. They were organized in topical sections as follows: Modeling Behaviour and Emotions; Hybrid Continuous-discrete Systems; Structure Learning; Multi-agent Systems; Epistemic Sampling; Robot Control; and Sustainability and Contextuality.

Full Product Details

Author:   Christopher L. Buckley ,  Daniela Cialfi ,  Pablo Lanillos ,  Riddhi J. Pitliya
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Volume:   2193
ISBN:  

9783031771378


ISBN 10:   3031771370
Pages:   290
Publication Date:   13 December 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

.- Modeling behaviour and emotions. .- Towards Interaction Design with Active Inference: A Case Study on Noisy Ordinal Selection. .- Modelling Agency Perception in Depression Using Active Inference: A Multi-Agent Behavioural Study. .- Free Energy in a Circumplex Model of Emotions. .- Hybrid continuous-discrete systems. .- Learning in Hybrid Active Inference Models. .- Learning and embodied decisions in active inference. .- Structure learning. .- Online Structure Learning with Dirichlet Processes through Message Passing. .- Exploring and Learning Structure: Active Inference Approach in Navigational Agents. .- Multi-agent systems. .- Belief sharing: a blessing or a curse. .- Coupled autoregressive active inference agents for control of multi-joint dynamical systems. .- Reactive Environments for Active Inference Agents with RxEnvironments. .- Epistemic sampling. .- Selection of Exploratory or Goal-Directed Behavior by a Physical Robot Implementing Deep Active Inference. .- Epistemic Value Anticipation into the Deep Active Inference Model. .- Robot control. .- Planning to avoid ambiguous states through Gaussian approximations to non-linear sensors in active inference agents. .- Message Passing-based Bayesian Control of a Cart-Pole System. .- Reducing Intuitive-Physics Prediction Error through Playing. .- Sustainability and contextuality. .- Modeling Sustainability under Active Inference through resource management. .- Contextuality, Cognitive engagement, and Active Inference.

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