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Introduction to computational cognitive modeling

In The Cambridge handbook of computational psychology. New York: Cambridge University Press. pp. 3--19 (2008)

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  1. The importance of cognitive architectures: An analysis based on CLARION.Ron Sun - unknown
    Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...)
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  • Cognitive and Computational Complexity: Considerations from Mathematical Problem Solving.Markus Pantsar - 2019 - Erkenntnis 86 (4):961-997.
    Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...)
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  • Lost in dissociation: The main paradigms in unconscious cognition.Luis M. Augusto - 2016 - Consciousness and Cognition 42:293-310.
    Contemporary studies in unconscious cognition are essentially founded on dissociation, i.e., on how it dissociates with respect to conscious mental processes and representations. This is claimed to be in so many and diverse ways that one is often lost in dissociation. In order to reduce this state of confusion we here carry out two major tasks: based on the central distinction between cognitive processes and representations, we identify and isolate the main dissociation paradigms; we then critically analyze their key tenets (...)
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  • The Place of Modeling in Cognitive Science.James L. McClelland - 2009 - Topics in Cognitive Science 1 (1):11-38.
    I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential—through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; (...)
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  • Production of Referring Expressions for an Unknown Audience: A Computational Model of Communal Common Ground.Roman Kutlak, Kees van Deemter & Chris Mellish - 2016 - Frontiers in Psychology 7.
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  • On humans' (explicit) intuitions about the meaning of novel words.Daniele Gatti, Francesca Rodio, Luca Rinaldi & Marco Marelli - 2024 - Cognition 251 (C):105882.
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  • Modeling the Effects of Perceptual Load: Saliency, Competitive Interactions, and Top-Down Biases.Kleanthis Neokleous, Andria Shimi & Marios N. Avraamides - 2016 - Frontiers in Psychology 7.
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  • Personalizing Human-Agent Interaction Through Cognitive Models.Tim Schürmann & Philipp Beckerle - 2020 - Frontiers in Psychology 11.
    Cognitive modeling of human behavior has advanced the understanding of underlying processes in several domains of psychology and cognitive science. In this article, we outline how we expect cognitive modeling to improve comprehension of individual cognitive processes in human-agent interaction and, particularly, human-robot interaction (HRI). We argue that cognitive models offer advantages compared to data-analytical models, specifically for research questions with expressed interest in theories of cognitive functions. However, the implementation of cognitive models is arguably more complex than common statistical (...)
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