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Causal understanding in reasoning about the world

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Methodologies for Intelligent Systems (ISMIS 1994)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 869))

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Abstract

In this paper I survey over a decade of work on how we understand how things work. Much of this work has been conducted in the context of reasoning about functions of devices. I briefly overview a representational framework called Functional Representation, and indicate how a device representation in this language can be used for simulation, diagnosis and design. I make remarks about the generality of this approach in terms of causal understanding.

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Authors and Affiliations

  1. Laboratory for AI Research, The Ohio State University, 43210, Columbus, OH, USA

    B. Chandrasekaran

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  1. B. Chandrasekaran
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Zbigniew W. Raś Maria Zemankova

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© 1994 Springer-Verlag Berlin Heidelberg

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Chandrasekaran, B. (1994). Causal understanding in reasoning about the world. In: Raś, Z.W., Zemankova, M. (eds) Methodologies for Intelligent Systems. ISMIS 1994. Lecture Notes in Computer Science, vol 869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58495-1_2

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  • DOI: https://doi.org/10.1007/3-540-58495-1_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58495-7

  • Online ISBN: 978-3-540-49010-4

  • eBook Packages: Springer Book Archive

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