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Artificial Intelligence and High-Level Cognition

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A Guided Tour of Artificial Intelligence Research

Abstract

Artificial intelligence (AI) and cognitive science (CS) both investigate information processing, but with a different focus: AI aims to build problem solving machines, i.e., systems capable of solving diverse problems in an efficient and effective way while CS analyzes human cognition. Both approaches increase an understanding of the foundations, methods, and strategies that can be employed to perform in a natural or artificial environment. This chapter focuses on high-level cognition, i.e., cognitive processes that are related to reasoning, decision making, and problem solving. After an introduction to the core principles, intersections, and differences between both fields, some central psychological findings are presented. In a next step cognitive theories for high-level cognition are introduced. While the architecture of cognition has an impact too, main approaches for cognitive modeling from cognitive architectures to multinomial processing trees are analyzed. Current challenges conclude the chapter.

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Acknowledgements

The author is grateful to Bernhard Nebel (University of Freiburg), Emmanuelle-Anna Dietz Saldanha (TU Dresden), and Nicolas Riesterer (University of Freiburg) for their substantial feedback.

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Authors and Affiliations

  1. Cognitive Computation Lab, Technical Faculty, University of Freiburg, Freiburg im Breisgau, Germany

    Marco Ragni

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Editors and Affiliations

  1. CRIL-CNRS, Université d'Artois and Institut Universitaire de France, Lens, France

    Pierre Marquis

  2. Aix Marseille Université, Université de Toulon, CNRS, LIS, Marseille, France

    Odile Papini

  3. IRIT, CNRS and Université Paul Sabatier, Toulouse, France

    Henri Prade

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Ragni, M. (2020). Artificial Intelligence and High-Level Cognition. In: Marquis, P., Papini, O., Prade, H. (eds) A Guided Tour of Artificial Intelligence Research. Springer, Cham. https://doi.org/10.1007/978-3-030-06170-8_14

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