A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probalistic reasoners, including Pei Wang's non-axiomatic reasoning system, Novamente's probabilistic logic network, which tip their hat to reasoning Bayesian networks, and Pronto[1] - probabilistic Description logic rea
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| - A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probalistic reasoners, including Pei Wang's non-axiomatic reasoning system, Novamente's probabilistic logic network, which tip their hat to reasoning Bayesian networks, and Pronto[1] - probabilistic Description logic rea
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| abstract
| - A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probalistic reasoners, including Pei Wang's non-axiomatic reasoning system, Novamente's probabilistic logic network, which tip their hat to reasoning Bayesian networks, and Pronto[1] - probabilistic Description logic reasoner.
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