Comparing two context-driven approaches for representation of human tactical behavior

    Authors

    A. J. Gonzalez;P. Brezillon

    Comments

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    Abbreviated Journal Title

    Knowl. Eng. Rev.

    Keywords

    GRAPHS; Computer Science, Artificial Intelligence

    Abstract

    This paper describes an investigation that compared Context-based Reasoning (CxBR) and Contextual Graphs (CxG), two well-known context-driven approaches used to represent human intelligence and decision-making. The specific objective of this investigation was to compare and contrast both approaches to increase the readers' understanding of each approach. We also identify which, if any, excels in a particular area, and to look for potential synergism between them. This comparison is presented according to 10 different criteria, with some indication of which one excels at each particular facet of performance. We focus the comparison on how each would represent human tactical behavior, either in a simulation or in the real world. Conceptually, these two context-driven approaches are not at the same representational level. This could provide an opportunity in the future to combine them synergistically.

    Journal Title

    Knowledge Engineering Review

    Volume

    23

    Issue/Number

    3

    Publication Date

    1-1-2008

    Document Type

    Review

    Language

    English

    First Page

    295

    Last Page

    315

    WOS Identifier

    WOS:000260272400004

    ISSN

    0269-8889

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