Overview: Carnegie-Mellon University scientists Herbert Simon and Allen Newell have investigated human problem-solving processes for many decades. One of their ideas, the production system, represents knowledge as a set of condition-action rules (also called "if-then rules"). If the conditions for a rule are satisfied, the rule's specified action occurs. In the late 70s, Charles Forgy developed OPS5, a programming language which embodies this idea. The production system became the dominant knowledge representation methodology in expert systems, and OPS5 became popular among expert system developers. OPS5 stores data in working memory, and if-then rules in production memory. Rules in OPS5 are completely independent of one another. They can be placed in production memory in any order. If the data in working memory match the conditions of a rule in production memory, the rule's actions take place. Possible actions include modifying the contents of working memory (which might then match the conditions of another rule), reading information from a file, displaying information on the screen, and calling external programs. In some versions of the language, a rule's actions can cause a new rule to be created, allowing the development of systems that learn.

OPS5's built-in inference mechanism, forward chaining, starts from a set of data in working memory and causes a sequence of rules to be applied until a goal is satisfied. The other prominent expert system inferencing procedure is backward chaining, in which a goal to be achieved causes subgoals to be satisfied until a problem solution is found. Backward chaining can be implemented in OPS5 with some work. (Reference: LANGUAGES OF AI by Joseph Schmuller, September/October 1991, page 21)

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