Semantic reasoner

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 logic 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 probabilistic reasoners, including non-axiomatic reasoning systems,[1] and probabilistic logic networks.[2]

"Reasoner" redirects here. For other uses, see Reasoner (disambiguation).

Notable applications

Notable semantic reasoners and related software:

Free to use (closed source)
  • Cyc inference engine, a forward and backward chaining inference engine with numerous specialized modules for high-order logic.
  • KAON2 is an infrastructure for managing OWL-DL, SWRL, and F-Logic ontologies.

Free software (open source)
  • Cwm, a forward-chaining reasoner used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, and it uses RDF/XML or N3 serializations as required.
  • Drools, a forward-chaining inference-based rules engine which uses an enhanced implementation of the Rete algorithm.
  • Flora-2, an object-oriented, rule-based knowledge-representation and reasoning system.
  • Jena, an open-source semantic-web framework for Java which includes a number of different semantic-reasoning modules.
  • Prova, a semantic-web rule engine which supports data integration via SPARQL queries and type systems (RDFS, OWL ontologies as type system).

Applications that contain reasoners
gollark: *More* software?
gollark: I can't really *use* kMarx anyway, because it's incompatible with Dragon. It uses chests directly and quite weirdly.
gollark: Then the kMarx licensing debates started, and I began work on kristshop, never to finish.
gollark: It *did*.
gollark: Well, basically, storage system access, assuming you occasionally do useful things.

See also

References
  1. Wang, Pei. "Grounded on Experience Semantics for intelligence, Tech report 96". www.cogsci.indiana.edu. CRCC. Retrieved 13 April 2015.
  2. Goertzel, Ben; Iklé, Matthew; Goertzel, Izabela Freire; Heljakka, Ari (2008). Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference. Springer Science & Business Media. p. 42. ISBN 9780387768724.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.