{{Short description|Software able to infer logical consequences}} {{Redirect|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,<ref name=Wang>{{cite web | last1=Wang | first1=Pei | title=Grounded on Experience Semantics for intelligence, Tech report 96 | url=http://www.cogsci.indiana.edu/pub/wang.semantics.ps | website=www.cogsci.indiana.edu | publisher=CRCC | access-date=13 April 2015}}</ref> and probabilistic logic networks.<ref name=Goertzel2008>{{cite book | last1=Goertzel | first1=Ben | last2=Iklé | first2=Matthew | last3=Goertzel | first3=Izabela Freire | last4=Heljakka | first4=Ari | title=Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference | date=2008 | publisher=Springer Science & Business Media | isbn=978-0-387-76872-4 | page=42}}</ref>
== Applications == <!--Entries should have a sourced Wikipedia article or some significant independent sources. Wikipedia is not a Github directory.--> 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. * [https://www.evrete.org/ Evrete], a forward-chaining Java rule engine that uses the Rete algorithm and is compliant with the Java Rule Engine API (JSR 94). * [https://github.com/eyereasoner/eye EYE], a reasoning engine performing forward- and backward-chaining along Euler paths, supporting the Semantic Web Stack and implementing Notation3. * D3web, a platform for knowledge-based systems (expert systems). * 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. * [https://github.com/mdesalvo/OWLSharp OWLSharp], a lightweight and friendly .NET library for realizing intelligent Semantic Web applications. * [https://github.com/NRules/NRules NRules] a forward-chaining inference-based rules engine implemented in C# which uses an enhanced implementation of the Rete algorithm * Prova, a semantic-web rule engine which supports data integration via SPARQL queries and type systems (RDFS, OWL ontologies as type system). * [https://github.com/kodymoodley/defeasibleinferenceplatform DIP], Defeasible-Inference Platform (DIP) is a Web Ontology Language reasoner and Protégé desktop plugin for representing and reasoning with defeasible subsumption.<ref>Britz, K. and Varzinczak, I., (2018). Rationality and context in defeasible subsumption. In International Symposium on Foundations of Information and Knowledge Systems (pp. 114-132). Springer, Cham.</ref> It implements a Preferential entailment style of reasoning that reduces to "classical entailment" i.e., without the need to modify the underlying decision procedure.
=== Semantic Reasoner for Internet of Things (open-source) === [http://linkedopenreasoning.appspot.com/?p=slorv2 S-LOR (Sensor-based Linked Open Rules) semantic reasoner] S-LOR is under GNU GPLv3 license.
S-LOR (Sensor-based Linked Open Rules) is a rule-based reasoning engine and an approach for sharing and reusing interoperable rules to deduce meaningful knowledge from sensor measurements.
== See also == {{portal|Software}} * Business rules engine * Doxastic logic * Expert systems * Logic programming * Method of analytic tableaux * Solver
== References == {{reflist}}
== External links == * [https://www.w3.org/2001/sw/wiki/OWL/Implementations OWL 2 Reasoners listed on W3C SW Working Group homepage] * [http://www.w3.org/TR/rdf-sparql-query/ SPARQL Query Language for RDF] * Marko Luther, Thorsten Liebig, Sebastian Böhm, Olaf Noppens: [https://dx.doi.org/10.1007/978-3-642-02121-3_9 Who the Heck Is the Father of Bob?]. ESWC 2009: 66–80 * Jurgen Bock, Peter Haase, Qiu Ji, Raphael Volz. [http://www.aifb.uni-karlsruhe.de/WBS/pha/publications/owlbenchmark_07_2007.pdf Benchmarking OWL Reasoners]{{dead link|date=May 2018 |bot=InternetArchiveBot |fix-attempted=yes }}. [https://ceur-ws.org/Vol-350/paper1.pdf Mirror available]. In ARea2008 – Workshop on Advancing Reasoning on the Web: Scalability and Commonsense (June 2008) * Tom Gardiner, Ian Horrocks, Dmitry Tsarkov. [http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-189/submission_23.pdf Automated Benchmarking of Description Logic Reasoners]. Description Logics Workshop 2006
{{Semantic Web}}
Category:Rule engines Category:Knowledge representation Category:Knowledge engineering Category:Ontology (information science) Category:Semantic Web Category:Automated reasoning