Abstract
Joint or shared attention is a fundamental cognitive ability, which manifests itself in shared-attention episodes where two individuals attend to the same object in the environment. Network-oriented modeling provides an explicit framework for laying out this attentional process from the perspective of the individual initiating the episode. To this end, we describe an adaptive network with two reification levels and clearly explain the role of its states. We conclude with some suggestions for extending this modeling work and thinking about the potential use-cases of more developed models.
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Ercelik, D.F., Treur, J. (2022). A Controlled Adaptive Network Model for Joint Attention. In: Klimov, V.V., Kelley, D.J. (eds) Biologically Inspired Cognitive Architectures 2021. BICA 2021. Studies in Computational Intelligence, vol 1032. Springer, Cham. https://doi.org/10.1007/978-3-030-96993-6_12
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DOI: https://doi.org/10.1007/978-3-030-96993-6_12
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Online ISBN: 978-3-030-96993-6
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