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Rule-based programming attempts to derive execution instructions from a starting set of data and rules. This is a more indirect method than that employed by an imperative programming language , which lists execution steps sequentially.
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. [ 1 ] [ 2 ] [ 3 ] The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that ...
Rule-based languages instantiate rules when activated by conditions in a set of data. Of all possible activations, some set is selected and the statements belonging to those rules execute. Rule-based languages include: [ citation needed ]
While a rules-based system could be considered as having “fixed” intelligence, in contrast, a machine learning system is adaptive and attempts to simulate human intelligence.
Constraint Handling Rules: rule-based programming language. CLIPS: public domain software tool for building expert systems. JBoss Drools: an open-source business rule management system (BRMS). ILOG rules: a business rule management system. JESS: a rule engine for the Java platform - it is a superset of the CLIPS programming language.
The language provides rule-based programming for the automation of an expert system, and is often termed as an expert system shell. [1] In recent years, intelligent agent systems have also developed, which depend on a similar ability.
Rule-based programming – a network of rules of thumb that comprise a knowledge base and can be used for expert systems and problem deduction & resolution; Visual programming – manipulating program elements graphically rather than by specifying them textually (e.g. Simulink); also termed diagrammatic programming
The execution of the rules will often result in new facts or goals being added to the knowledge base, which will trigger the cycle to repeat. This cycle continues until no new rules can be matched. In the first step, match rules, the inference engine finds all of the rules that are triggered by the current contents of the knowledge base. In ...