Talk:Business rules engine
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- 1 Rule engine Vs Rules engine
- 2 Inference engine
- 3 Don't Merge
- 4 Requested move
- 5 Is it worth investing? - PHB comment
- 6 Too Java-centric?
- 7 Merge
- 8 Differentiate - vendor comment & stds developer comment
- 9 Notes on the term
- 10 Merge with Inference Engine?
- 11 Business rules produce knowledge; work flows perform business work.
- 12 Is this a joke?
- 13 File:Rule engine.png Nominated for speedy Deletion
- 14 Here's a little help with the history of rules
Rule engine Vs Rules engine
An Inference engine is a sub-category of a rule engine; they are not one-to-one and this is a cause of confusion for many people.
An inference engine may infer facts from existing facts/non-fact inputs. Business Rules Engines and Production Engines are based on the use of conditional rules. An inference engine may be constructed using rules. Howeve, a inference engine may be constructed using Neural Net and other technologies for pattern recognition to infer facts, and in such cases can include abductive logic. In which case it would clearly not be a Business Rules Engine nor would it be a Production Engine. In that respect, Business Rules Engine or Production Engine can be considered to be a sub catagory of an Inference Engine.18.104.22.168 (talk) 20:19, 9 June 2009 (UTC)
Business Rules Engine should not be moved to inference engines since business rules engines need not do inference at all. For example, in a business rules engine the system may check at a given time which rule applies given the system state and then applies the rule but the business rule need not modify the system state. Inference engines produce new data or modify old data that may effect the evaluation of other rules. —Preceding unsigned comment added by Jagan.chidella (talk • contribs) 21:06, 21 April 2010 (UTC)
JA: I requested admin assist to move Rule engine to Business rules engine for the reason given as "fit title to content and related articles, and to undo an ill-considered redirect", as a previous version of the content was initially under the title Business rules engine but subsequently redirected to this overly generic title, which is used more broadly in Artificial intelligence and not just in enterprise applications. Thank you, Jon Awbrey 16:36, 19 March 2006 (UTC)
Is it worth investing? - PHB comment
The consensus amongst the greater intellectual population out there is that this is worth it if you have money to throw around at resources to manage them. If you are not one for vestigial thought, then perhaps you should re-consider.
unsupported comments like this have no place in wikipedia. if you can provide real-world numbers as to why rules engines are more efficient or powerful or easy to maintain when compared to other languages, i'd love to see them. if not, then this should be removed.
--22.214.171.124 16:22, 6 April 2006 (UTC)
With the mention of JSR and POJOs, this page seems too biased towards java if this article is discussing business rule engines in general. Hertzsprung 15:24, 24 April 2007 (UTC)
- I don't have an issue with it mentioning JSRs and POJOs, however if there are other standard interfaces for other languages just add these to a standards section. The article just needs to be expanded for other languages.
Differentiate - vendor comment & stds developer comment
A BRE *could be* a production system (typically not in a BPM system though) and *could be* an inference engine (not in some Decision Table tools though and most BRMSs that optionally generate Java code rather than deploy to Rete...).
Notes on the term
Merge with Inference Engine?
Business rules produce knowledge; work flows perform business work.
Do you mean that business rule is itself knowledge and creates information (e.g. events)?
Is this a joke?
File:Rule engine.png Nominated for speedy Deletion
An image used in this article, File:Rule engine.png, has been nominated for speedy deletion for the following reason: All Wikipedia files with unknown copyright status
Don't panic; you should have time to contest the deletion (although please review deletion guidelines before doing so). The best way to contest this form of deletion is by posting on the image talk page.
Here's a little help with the history of rules
I'm going to try to help with some personal knowledge here, but I'll leave it to someone else to find the proper citations etc. I was out demonstrating a commercial rule based system at universities and national laboratories in 1985, so you can see that the Computerworld's estimate tracing “rules engines to the early 1990s” doesn't reach the beginning.
The earliest rule-based systems were developed at Standford University in the early 1980s by Bruce G. Buchanan and Edward H. Shortliffe. You can get a link to an early publication from Shortliffe's Wikipedia page. http://en.wikipedia.org/wiki/Edward_H._Shortliffe#References
I know at least that Bruce Buchanan was involved in early related work: http://en.wikipedia.org/wiki/Dendral It's odd that he doesn't seem to have a Wikipedia page. I never met Shortliffe.
In the early/mid 1980s I was working for Texas Instruments. This was the early days of Artificial Intelligence commercialization. At the time, rule processing was considered to be part of that “getting computers to do things that humans can do that currently computers don't do or don't do well” academic movement. One of the underlying innovations was to treat logic as data and separating it from a generic (not application specific) “processing engine”, so that all the application specific stuff was in a “knowledge base” and the generic processing code could be reused for untold thousands of different applications. There was a big thing at the time called “knowledge engineering” where one would extract knowledge from experts and try to formulate them into rules.
Texas Instruments built a commercial product based on their work. The first version was called “Personal Constultant” and then they created “Personal Constultant Plus.” The biggest difference between the two was that the first used a Lisp engine built by some guy (sorry my memory isn't that good) and the second used Scheme, an open-source PC based Lisp used in M.I.T. courses.
By the time I left TI in 1986, several other companies had rule systems available, including a database company that was forging ahead directly building interest for business rule type use with databases. There was also a cutting edge commercial effort by AI legand Edward Albert Feigenbaum, with a system called KEYE.
Found another reference of interest on Wikipedia, expert systems. They were “rule-based”: http://en.wikipedia.org/wiki/History_of_artificial_intelligence#The_rise_of_expert_systems
I'll come back later to see how the article is doing.