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Multidisciplinary Intersections on Artificial-Human Vividness: Phenomenology, Representation, and the Brain.
Molokopoy, Violetta; D'Angiulli, Amedeo.
Afiliação
  • Molokopoy V; Department of Neuroscience, Carleton University, Ottawa, ON K1S 5B6, Canada.
  • D'Angiulli A; Department of Neuroscience, Carleton University, Ottawa, ON K1S 5B6, Canada.
Brain Sci ; 12(11)2022 Nov 03.
Article em En | MEDLINE | ID: mdl-36358420
ABSTRACT
This article will explore the expressivity and tractability of vividness, as viewed from the interdisciplinary perspective of the cognitive sciences, including the sub-disciplines of artificial intelligence, cognitive psychology, neuroscience, and phenomenology. Following the precursor work by Benussi in experimental phenomenology, seminal papers by David Marks in psychology and, later, Hector Levesque in computer science, a substantial part of the discussion has been around a symbolic approach to the concept of vividness. At the same time, a similar concept linked to semantic memory, imagery, and mental models has had a long history in cognitive psychology, with new emerging links to cognitive neuroscience. More recently, there is a push towards neural-symbolic representations which allows room for the integration of brain models of vividness to a symbolic concept of vividness. Such works lead to question the phenomenology of vividness in the context of consciousness, and the related ethical concerns. The purpose of this paper is to review the state of the art, advances, and further potential developments of artificial-human vividness while laying the ground for a shared conceptual platform for dialogue, communication, and debate across all the relevant sub-disciplines. Within such context, an important goal of the paper is to define the crucial role of vividness in grounding simulation and modeling within the psychology (and neuroscience) of human reasoning.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article