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Symbolic & Classical AI

forward chaining

nounAlso: forward reasoning, data-driven reasoning, data-driven inference, forward-chain

In plain wordsA 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.

  1. An inference strategy for rule-based systemsrule-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. and logic programs that starts from the facts in working memory and repeatedly fires any rule whose conditions are all satisfied, adding its conclusion as a new fact (an application of modus ponens), until a goal is derived or no rule yields anything new (a fixpoint). It is data-driven: it computes what follows from the available data, which suits monitoring, configuration and settings where observations arrive continually, but it can waste effort deriving facts irrelevant to any question. For propositional Horn clausesHorn clause, n.: A simple, restricted form of logical rule ('if these conditions all hold, then this one conclusion holds') that computers can reason with very efficiently. it is complete and runs in time linear in the size of the knowledge base. Production-system interpreters such as OPS5 and CLIPS, DatalogDatalog, prop. n.: A small logic language for asking questions of a database with rules, including rules that refer to themselves, such as 'X is an ancestor of Y if X is a parent of an ancestor of Y'. engines and most business-rules engines chain forward.

    The fraud engine chains forward from each new transaction and raises an alert as soon as a pattern completes.

Origin

The forward–backward distinction appears in early theorem-proving and problem-solving programs of the late 1950s; the 'chaining' terminology became standard in the expert-system literature of the 1970s and 1980s, contrasting data-driven systems such as OPS5 with goal-driven ones such as MYCINMYCIN, prop. n.: A 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..

Related

See also
  • 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.
  • production systemproduction system, n.: A program built from many 'if this, then do that' rules plus a memory of current facts; it repeatedly finds a rule whose 'if' part matches and carries out its 'then' part.
  • 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.
  • DatalogDatalog, prop. n.: A small logic language for asking questions of a database with rules, including rules that refer to themselves, such as 'X is an ancestor of Y if X is a parent of an ancestor of Y'.
  • Horn clauseHorn clause, n.: A simple, restricted form of logical rule ('if these conditions all hold, then this one conclusion holds') that computers can reason with very efficiently.
Contrast with
  • 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.

Mentioned in

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., inferenceinference, n.: Drawing a conclusion from evidence. In today's AI it most often means running an already-trained model to get an answer, as opposed to training it., 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., 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., DatalogDatalog, prop. n.: A small logic language for asking questions of a database with rules, including rules that refer to themselves, such as 'X is an ancestor of Y if X is a parent of an ancestor of Y'., Horn clauseHorn clause, n.: A simple, restricted form of logical rule ('if these conditions all hold, then this one conclusion holds') that computers can reason with very efficiently., production systemproduction system, n.: A program built from many 'if this, then do that' rules plus a memory of current facts; it repeatedly finds a rule whose 'if' part matches and carries out its 'then' part., 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.