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2023 | OriginalPaper | Buchkapitel

The Role of Valence and Meta-awareness in Mirror Self-recognition Using Hierarchical Active Inference

verfasst von : Jonathan Bauermeister, Pablo Lanillos

Erschienen in: Active Inference

Verlag: Springer Nature Switzerland

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Abstract

The underlying processes that enable self-perception are crucial for understanding multisensory integration, body perception and action, and the development 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 affect using state-of-the-art hierarchical active inference. We evaluated our model in a synthetic experiment inspired by the mirror self-recognition test, a benchmark for evaluating self-recognition in animals and humans alike. Results show that i) negative valence arises when the agent recognizes itself and learns something unexpected about its internal states. Furthermore, ii) the agent in the presence of strong prior expectations of a negative affective state will avoid the mirror altogether in anticipation of an undesired learning process. Both results are in line with current literature on human self-recognition.

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Vorheriges Kapitel Mapping Husserlian Phenomenology onto Active Inference

Nächstes Kapitel World Model Learning from Demonstrations with Active Inference: Application to Driving Behavior

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For a thorough tutorial on discrete active inference formulation see [21] and for a concise mathematical overview see [5].

Using the discrete space formulation of active inference in matrix form this is computed by selecting the right column of the matrix A, i.e., through a one-hot observational vector.

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Titel: The Role of Valence and Meta-awareness in Mirror Self-recognition Using Hierarchical Active Inference
verfasst von: Jonathan Bauermeister
Pablo Lanillos
Verlag: Springer Nature Switzerland
Buch: Active Inference
Print ISBN: 978-3-031-28718-3

Electronic ISBN: 978-3-031-28719-0

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-28719-0_8

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