MYCIN
In plain wordsA 1970s Stanford program that advised doctors on blood infections and antibiotics by applying hundreds of if–then rules from specialists. It performed about as well as experts but was never used on patients.
A rule-basedrule-based system, n.: A computer system that makes decisions by following a list of 'if… then…' rules written by people, rather than by learning from examples. expert systemexpert system, n.: A program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers. built at Stanford University in the 1970s to advise physicians treating serious bacterial infections, such as bacteremia and meningitis, on the likely organism and on which antibiotics to give at what doses. It held several hundred if–then rules gathered from infectious-disease specialists and applied them by backward chainingbackward chaining, n.: A way of reasoning that starts from the question ('is this true?') and works backward, looking for rules that would prove it and then checking whether their conditions hold.: its inference engineinference engine, n.: The part of an AI system that does the working-out: in older AI, the program that applies rules to facts; in today's AI, the software that runs a trained model to produce answers. started from candidate diagnoses and questioned the physician whenever it needed a fact. Uncertain evidence was handled by attaching a certainty factor to each rule and combining these with an ad hoc calculus rather than probability theory, and the system could justify itself by answering why-and-how questions about the rules it had used. In a blinded comparison published in 1979, evaluators found its treatment recommendations acceptable at least as often as those of Stanford infectious-disease faculty. It never entered clinical use, held back by problems of integration, liability and ethics.
MYCIN's certainty factors were an early, informal answer to the problem of reasoning under uncertainty.
Origin
Created by Edward Shortliffe for his doctoral work, with Bruce Buchanan, Stanley Cohen and others, and described in his book Computer-Based Medical Consultations: MYCIN (1976). The name comes from the suffix -mycin of many antibiotic names. Its domain-independent shell, EMYCIN ('Essential MYCIN'), became a template for later expert systems.
Related
- expert systemexpert system, n.: A program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers.
- DENDRALDENDRAL, prop. n.: A program begun at Stanford in 1965 that worked out the structure of chemical molecules from laboratory measurements using rules taken from expert chemists. It is usually called the first expert system.
- backward chainingbackward chaining, n.: A way of reasoning that starts from the question ('is this true?') and works backward, looking for rules that would prove it and then checking whether their conditions hold.
- inference engineinference engine, n.: The part of an AI system that does the working-out: in older AI, the program that applies rules to facts; in today's AI, the software that runs a trained model to produce answers.
- knowledge baseknowledge base, n.: A store of facts and rules that a program can reason with: like a database, but organized so that new conclusions can be worked out from it, not just looked up.
- rule-based systemrule-based system, n.: A computer system that makes decisions by following a list of 'if… then…' rules written by people, rather than by learning from examples.
Sources
- Shortliffe, E. H. (1976). Computer-Based Medical Consultations: MYCIN. New York: Elsevier.
- Buchanan, B. G. & Shortliffe, E. H. (eds.) (1984). Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley.
Mentioned in
explainable AIexplainable AI, n.: The field and set of methods that let people understand why an AI system produced a particular output — for example, which factors led it to reject a loan application., backward chainingbackward chaining, n.: A way of reasoning that starts from the question ('is this true?') and works backward, looking for rules that would prove it and then checking whether their conditions hold., Edward FeigenbaumEdward Feigenbaum, prop. n.: An American computer scientist who pioneered expert systems, programs that capture specialists' knowledge as rules to solve problems in fields such as chemistry and medicine., expert systemexpert system, n.: A program that stores a human specialist's know-how as many if–then rules and uses them to give advice or make decisions in a narrow field, such as diagnosing infections or configuring computers., forward chainingforward chaining, n.: A way of reasoning that starts from known facts and keeps applying rules to them, adding each new conclusion, until it reaches an answer or nothing new can be concluded., knowledge baseknowledge base, n.: A store of facts and rules that a program can reason with: like a database, but organized so that new conclusions can be worked out from it, not just looked up., LispLisp, prop. n.: A programming language invented in 1958 for AI research, in which programs and data are written the same way, as nested lists in parentheses. It was the main language of AI for decades., rule-based systemrule-based system, n.: A computer system that makes decisions by following a list of 'if… then…' rules written by people, rather than by learning from examples., Dempster–Shafer theoryDempster–Shafer theory, n.: A theory of reasoning with uncertain evidence that lets you hold back belief — in effect saying 'I don't know' — instead of being forced to divide all your confidence among the possibilities., DENDRALDENDRAL, prop. n.: A program begun at Stanford in 1965 that worked out the structure of chemical molecules from laboratory measurements using rules taken from expert chemists. It is usually called the first expert system., knowledge engineeringknowledge engineering, n.: The craft of collecting what human experts know — through interviews, observation and documents — and turning it into rules or structured data that a computer system can use., XCONXCON, prop. n.: A rule-based program used from 1980 by the computer maker Digital Equipment Corporation to work out which parts each customer's computer order needed. It was the first big commercial success of expert systems.