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Conference of the Canadian Society for Computational Studies of Intelligence

Canadian AI 1996: Advances in Artifical Intelligence pp 1–13Cite as

Constraint-directed improvisation for complex domains

  • Knowledge Representation I: Constraints
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1081))

Abstract

We present Waffler, a novel architecture that allows an agent to perform in complex, dynamic environments in a timely manner through improvisation. Improvisation involves using a routine method of accomplishing an activity as a guide to satisficing behaviour, adhering to that method as closely as the current situation permits for economic reasons, and exploring the background knowledge from which the routine has arisen to supplement the routine and move beyond it when necessary. Agents employing this approach can follow a routine in the face of uncertainty and variability, and can apply a routine in a situation with novel aspects, satisficing to the degree that time is available. This paper describes the Waffler architecture's basis in constraint-directed reasoning, it's knowledge structures and processing mechanisms, and an implementation in a simulated environment.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Manitoba, R3T 2N2, Winnipeg, Manitoba, Canada

    John Anderson & Mark Evans

Authors
  1. John Anderson
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  2. Mark Evans
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Editor information

Gordon McCalla

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© 1996 Springer-Verlag Berlin Heidelberg

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Anderson, J., Evans, M. (1996). Constraint-directed improvisation for complex domains. In: McCalla, G. (eds) Advances in Artifical Intelligence. Canadian AI 1996. Lecture Notes in Computer Science, vol 1081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61291-2_37

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  • DOI: https://doi.org/10.1007/3-540-61291-2_37

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61291-9

  • Online ISBN: 978-3-540-68450-3

  • eBook Packages: Springer Book Archive

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