Abstract
In this paper I shall describe the symbolic search space paradigm which is the dominant model for most of AI. Coupled with the mechanisms of logic it yields the predominant methodology underlying expert systems which are the most successful application of AI technology to date. Human decision making, more precisely, expert human decision making is the function that expert systems aspire to emulate, if not surpass.
Expert systems technology has not yet proved to be a decisive success — it appears to fare better in some areas of human expertise than others. As a result subdomains of human expertise are variously categorised and we shall examine a few of the suggested classification schemes. A particular line of argument explored is one which maintains that certain types of human decision making, at least, are not adequately approximated by the symbolic search space paradigm of AI. Furthermore, attempts to project this inadequate model of human decision making via implementations of expert systems will be detrimental to both our image of ourselves and the future possibilities for AI software.
Finally, we examine one possible route to the realization of AI, perhaps even practical applications of AI, that is a significant alternative to the model offered by the symbolic search space paradigm.
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Partridge, D. Human decision making & the symbolic search space paradigm in AI. AI & Soc 1, 103–114 (1987). https://doi.org/10.1007/BF01891271
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DOI: https://doi.org/10.1007/BF01891271