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Additional resources for Applications of Artificial Intelligence for Organic Chemistry: The Dendral Project (McGraw-Hill advanced computer science series)
In the case of a continuous function of two variables, the plot of the function is a surface and the problem is to find the peak of the highest hill on that surface. By moving in the direction of steepestascent (readily determined if the function is differentiable), the search climbs to the top of the nearest hill. The strengths and weaknessesof this method are readily apparent from this image. Local maxima (peaks and mesas) capture the climber who can not descend to find a higher hill. Methods to select starting points are crucial, therefore, and it is advisable to use more than one starting point.
At the very least there will be some information about its source and extraction methods, which often suggestsprobable constituents. Laboratory analyses may also provide further clues of this sort. In addition other instrument-based techniques provide information about the compound. The most common among these are gas chromatography, infrared spectrometry, ultraviolet spectrometry, and nuclear magnetic resonance specfrometry (NMR). At the time of writing DENDRAL has not been extended to the interpretation of these data [with one exception, Carhart and Djerassi (1973)] in the way it interprets MS data.
Scientists would find the above formulation of their problem a poor characterization of their own activity. Furthermore, an intuitively conceived problem can always be forced into the paradigm in a number of ways and the representation chosen will often make the difference between trivial and impossible. We know of no nontrivial exceptions to the claim that all AI problem-solving approaches have finessed this representation problem by leaving it to the human programmer/scientist. Nonetheless there are many problems that fit naturally into the paradigm, and for which an appropriate representation is available.