Editing Inference engine (section)

==Implementations==
Early inference engines focused primarily on forward chaining. These systems were usually implemented in the [[Lisp (programming language)|Lisp]] programming language. Lisp was a frequent platform for early AI research due to its strong capability to do symbolic manipulation. Also, as an [[interpreted language]] it offered productive development environments appropriate to [[debugging]] complex programs. A necessary consequence of these benefits was that Lisp programs tended to be slower and less robust than compiled languages of the time such as [[C (programming language)|C]]. A common approach in these early days was to take an expert system application and repackage the inference engine used for that system as a re-usable tool other researchers could use for the development of other expert systems. For example, [[MYCIN]] was an early expert system for medical diagnosis and EMYCIN was an inference engine extrapolated from MYCIN and made available for other researchers.<ref name="Hayes-Roth 1983" />

As expert systems moved from research prototypes to deployed systems there was more focus on issues such as speed and robustness. One of the first and most popular forward chaining engines was [[OPS5]], which used the [[Rete algorithm]] to optimize the efficiency of rule firing. Another very popular technology that was developed was the [[Prolog]] logic programming language. Prolog focused primarily on backward chaining and also featured various commercial versions and optimizations for efficiency and robustness.<ref>{{cite book|last=Sterling|first=Leon|title=The Art of Prolog|year=1986|publisher=MIT|location=Cambridge, MA|isbn=0-262-19250-0|author2=Ehud Shapiro|url=https://archive.org/details/artofprologadvan00ster}}</ref>

As expert systems prompted significant interest from the business world, various companies, many of them started or guided by prominent AI researchers created productized versions of inference engines. For example, [[IntelliCorp (software)|Intellicorp]] was initially guided by [[Edward Feigenbaum]]. These inference engine products were also often developed in Lisp at first. However, demands for more affordable and commercially viable platforms eventually made [[personal computer]] platforms very popular.

===Open source implementations===

[https://clipsrules.net/ ClipsRules] and [http://refpersys.org RefPerSys] (inspired by [https://github.com/bstarynk/caia-pitrat CAIA] <ref>{{cite book|last=Pitrat|first=Jacques|title=Artificial Beings, the conscience of a conscious machine|year=2009|publisher=Wiley|isbn=978-1848211018}}</ref> and the work of [[Jacques Pitrat]]). The [https://frama-c.com/ Frama-C] static source code analyzer also uses some inference engine techniques.