Abstract
Artificial intelligence (AI) applications are often faulted for their brittleness and slowness. In this paper, we argue that both of these problems can be ameliorated if the AI program is context-sensitive, making use of knowledge about the context it is in to guide its perception, understanding, and action. We describe an approach to this problem, context-mediated behavior (CMB). CMB uses contextual schemas (c-schemas) to explicitly represent contexts. Features of the context are used to find the appropriate c-schemas, whose knowledge then guides all aspects of behavior.
This work was funded in part by the United States National Science Foundation under grant BES-9696044.
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© 1998 Springer-Verlag
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Turner, R.M. (1998). Context-mediated behavior for AI applications. In: Mira, J., del Pobil, A.P., Ali, M. (eds) Methodology and Tools in Knowledge-Based Systems. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64582-9_785
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DOI: https://doi.org/10.1007/3-540-64582-9_785
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