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.
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.
Produktdetails
Produktdetails
Communications in Computer and Information Science 2193
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Inhaltsangabe
.- 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.
.- 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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