Titlebook: Active Inference; Third International Christopher L. Buckley,Daniela Cialfi,Tim Verbelen Conference proceedings 2023 The Editor(s) (if app

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后來(lái)

https://doi.org/10.1007/978-981-99-4929-8opment of the self. Previous computational models have overlooked an essential aspect: affective or emotional components cannot be uncoupled from the self-recognition process. Hence, here we propose a computational approach to study self-recognition that incorporates . using state-of-the-art hierarc

Adornment

https://doi.org/10.1007/978-981-99-4929-8the active inference literature, world models are typically pre-specified or learned through interacting with an environment. This paper explores the possibility of learning world models of active inference agents from recorded demonstrations, with an application to human driving behavior modeling.

細(xì)胞膜

Occupational Safety and Health,present Active Blockference, an approach for cognitive modeling in complex cyberphysical systems that uses cadCAD to implement multiagent Active Inference simulations. First, we provide an account of the current state of Active Inference in cognitive modeling, with the Active Entity Ontology for Sci

凝結(jié)劑

Occupational Safety and Health, understand value functions in terms of Bayesian posteriors. An alternative, but less explored, model-free RL algorithm is the successor representation, which expresses the value function in terms of a successor matrix of average future state transitions. In this paper, we derive a probabilistic int

implore

Mindfulness

Sonja Boon,Lesley Butler,Daze Jefferiesce early in life of human beings, the present work aims at exploring a possible approach to attachment, exploiting some aspects deriving from the Active Inference Theory. We describe how, from the prenatal stage until around the second year of life, the sensory, relational, affective and emotional d

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JOT

Sonja Boon,Lesley Butler,Daze Jefferiese labyrinth searching for rewards, returning to their home cage now and then, e.g. to drink. Surprisingly, when executing such a “home run”, the mice do not follow the exact reverse path, in fact, the entry path and home path have very little overlap. Recent work proposed a hierarchical active infer

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