Glauber

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Glauber is a discovery system type of artificial intelligence that is used to discover new chemical theories based on empirical evidence and the systematic measurement of related data. It is named after Johann Rudolph Glauber, a chemist in the 18th century whose work helped to develop acid-base theory. Glauber was designed by Pat Langley as part of his work on discovery heuristics in an attempt to have a computer automatically review a host of values and characteristics and make independent analyses from them. In the case of Glauber, the goal was to have an autonomous application that could estimate or even perfectly describe the nature of a given chemical compound by comparing it to related substances. Langley formalized and compiled Glauber in 1983. It was supplied information about a variety of materials as they had been described by 18th century chemists, before most of modern chemical knowledge had been uncovered or invented. Descriptions like taste rather than numerical measures such as molecular weight were programmed into the application. Chemical reactions that were known in that era and the distinction between reactants and products were also provided. From this knowledge, Glauber was to figure out which substances were acids, bases, and salts without any qualitative information at all. The system examines chemical substances and all of their most likely reactions and correlates the expected taste and related acidity or saltiness according to the rule that acids and bases produce salts. Glauber was a very successful advance in theoretical chemistry as done by a computer program, and it, along with similar systems developed by Herbert Simon including Stahl (which examines oxidation) and DALTON (which calculates atomic weight) helped form the groundwork of all current automated chemical analysis.