[rules-dev] Naive questions on rules

Thu Oct 23 09:17:15 EDT 2008

Hi Ellen Zhao,

Thanks a mill for answering my question. You answer do helps a lot. I ll 
put questions like this to other mail list next time, and sorry for the 
inconvenience I caused.

Best Regards
Wei Tai

Ellen Zhao wrote:
> Hi Wei Tai,
>
>
> So here I try to answer your questions "from a very high level of view" :-D
>
> An expert system uses deduction, abduction and induction as
> inferencing mechanisms.
> The interaction between knowledge base and inference engine can be
> summarized as follows:
>
>  * deduction: cause + rule  ----> effect
>  * abduction: effect + rule  ----> cause
>  * induction: cause + effect ----> rule
>
> Inference engines that implement deduction are called forward-chaining
> inference engines,
> those implement abduction are called backward-chaining inference
> engines. They are also
> understood as data-driven and goal-driven inference engines. Many
> modern inference engines
> are hybrid engines, as many problems require both deduction and
> abduction for their
> solutions. The induction, however, happens usually in knowledge
> acquisition components
> and heavily employs pattern recognition and machine learning
> techniques such as Bayesian
> Nets and Artificial Neural Nets.
>
> *You need to know what your application exactly wants to achieve and
> then apply different styles of inference.*
>
> Expert systems enable domain experts and software engineers to program
> declaratively. Both facts and rules can be declared without any
> particular order (only specifying what but not how). This has two
> major benefits:
>
> 1. Facts and rules can be organized in any order or structure that
> better reflects the
> semantic of the problem.
> 2. Ignoring the sequences of facts and rules may significantly reduce
> a developer's cognitive
> load, therefore increases her efficiency and reduce her errors during
> engineering.
>
> But no problem can be solved if the application contains only
> declarations. The "declarative
> programming" only largely applies in the knowledge base. Normally, an
> inference engine is strictly algorithmic, which means it must be
> programmed procedurally. It is also an over-generalization to think
> that all knowledge bases contains only declarations and all
> inference engines only procedures. In practice, the "then" part of a
> rule declaration often
> contains procedures, more or less. Also, there are inference engines
> progammed declaratively in languages such as Prolog. Nevertheless,
> eventually all declarative instructions are translated into procedural
> machine code. In fact, the declarative programming model has nothing
> to contribute to a program's run-time performance but it may
> dramatically increase the performance of domain experts, software
> engineers, and information managers.
>
> The "if-then"-like rules are a type of production whose orgins go back
> to the 1940s.
> Production systems were first used in symbolic logic by Emil L. Post
> who originated the
> name. Post proved that any system of mathematics or logic is
> equivalent to a certain type
> of production rule system. This result established the great
> possibility of representing most kinds of knowledge in a canonical,
> if-thenlike form. Post's production rule system was never really
> practical because it lacked the specification guiding how the rules
> should be applied. When facts meet rules, should a fact seek
> applicable rules or should a rule seek suitable facts? No matter which
> strategy we choose, then in what kind of order should facts and rules
> match each other?
>
> In 1960, Andrey A. Markov published his string rewrite algorithm,
> which is a control
> strategy of how rules should be applied in a production system. The
> Markov algorithm
> organizes the rules in order of priority, with higher-priority rules
> ordered first. Given a
> string that is to be rewritten, the whole list of rules is scanned
> from the beginning to the end
> whenever a to-be-substituted symbol occurs in the string. Although
> directly the Markov
> Algorithm is only about string rewrite, most problems are in fact
> encoded as strings for
> computation. Therefore, this algorithm made the beautiful Post theorem
> practical.
>
> In practice, new problems arose when people put more and more rules
> and facts into
> knowledge bases. Modern knowledge bases usually contain hundreds,
> thousands or tens
> of thousands of rules. If the whole list of rules is iterated whenever
> there is a fact to
> be examed (the Markov Algorithm's principle: fact seeks the rules),
> the system performs
> poor. In the late 1970s, some production systems spent more than 90%
> of the total run
> time performing rules-iteration. In 1979, Charles L. Forgy invented
> the Rete Algorithm to increase the pattern-matching efficiency of
> production systems. The Rete Algorithm solved the scalability problem
> of modern production systems, was then widely implemented in many
> expert systems. Many variants of Forgy's original algorithm, such as
> Rete II, Rete III, and ReteOO, were spawned.
>
> I hope this explanation is high-level enough. Please refer to Drools
> docs, papers and books if you want to know more about different
> algorithms.
>
> And BTW, you better post such kind of questions to the rules-user
> mailing list. This dev list is for the development-related topics of
> the Drools project, it is normally for stuff like "Hi the svn 24567
> does not build, there is a problem in the pom.xml in the package
> org.drools.guvnor.etc,  I've submitted a JIRA with a patch, please
> have a look.....".
>
>
> Best Regards,
> Ellen N. Zhao
>
>
> On Thu, Oct 23, 2008 at 12:41 PM, Wei Tai <taiw at cs.tcd.ie> wrote:
>   
>> Hi Ellen Zhao,
>>
>> Thank you for pointing me a way to digging into the rule and rule systems.
>> Maybe I didn't explain myself clearly enough. My project is about
>> description logic and its reasoner. Part of this area uses rules but not
>> all, and currently I am going to understand this area from a very high level
>> of view. The way you point to me (to read a lot of books) do helps a lot,
>> but that requries lots of time before I can totally answer the question I've
>> put in the last mail, and besides, my project's plan does not allow me to do
>> this, at least now. I do searched on Google and Wikipedia a lot to find me
>> the answer. But the reality is "there are too many definitions on these
>> concepts (and some of them are really confusing), and seems little of them
>> can clearly state the relationships between each other(e.g. to give a
>> taxonomy or something like "this partly uses that but not all")". I believe
>> only people who know this area well can answer this question, isnt it? To
>> clarify, what I want to know is something like a taxonomy or an answer like
>> "logic programming is partly implemented by production system and the
>> production system uses forward chaining as its underlying inference
>> approach". I just took a look at the Drools document. It helps but still can
>> not answer my question well. Hope someone could help me out.
>>
>> Cheers
>> Wei Tai
>>
>>
>> Ellen Zhao wrote:
>>     
>>> Hi Wei Tai,
>>>
>>> first of all, there is a Chinese proverb "Give a man a fish and you
>>> feed him for a day. Teach a man to fish and you feed him for a
>>> lifetime.", so please allow me to mention that google and wikipedia
>>> are your good friends when you start to learn something. Here is a
>>> Wikipedia entry for Production Rule System:
>>>
>>> http://en.wikipedia.org/wiki/Production_system
>>>
>>> You can search for the other concepts yourself. And, the official
>>> Drools Documentation is exceptionally good, please by all means read
>>> it if you are new to expert system and Drools. Here you can download
>>> the latest Drools 5.0.0 M2 doc as a zip file:
>>>
>>> http://www.jboss.org/drools/downloads.html
>>>
>>> You will know from the web articles and Drools doc that there are good
>>> books for beginners. Grab the book list and go to your univ. lib or
>>> amazon.com, get a copy and invest time for reading.
>>>
>>> Hope that helps.
>>>
>>> Ellen N. Zhao
>>>
>>> On Wed, Oct 22, 2008 at 6:00 PM, Wei Tai <taiw at cs.tcd.ie> wrote:
>>>
>>>       
>>>> Hi All,
>>>>
>>>> I am not sure whether it is the right place to put this question here.
>>>> Currently I am working on rules and got confused with some concepts:
>>>>
>>>> What are the relationships between: resolution, backward chaining, modus
>>>> ponens, foward chaining, production rule system, prolog, logic
>>>> programming?
>>>> Can all forward chaining systems be considered as logic programming
>>>> system?
>>>>
>>>> Some of these concepts seems overlap with each other. Can somebody kindly
>>>> give me an answer to these questions. Thanks in advance.
>>>>
>>>>
>>>> Best Regards
>>>> Wei
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>>>> https://lists.jboss.org/mailman/listinfo/rules-dev
>>>>
>>>>
>>>>         
>>> _______________________________________________
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>>>
>>>       
>> --
>> Wei Tai
>> Student by Research, Knowledge & Data Engineering Research Group
>> Intelligent Systems Lab
>> School of Computer Science and Statistics
>> Trinity College Dublin
>> Dublin 2
>> Ireland
>>
>>     
>>> taiw at cs.tcd.ie
>>> Tel:  +353 (0)1 8968431
>>>       
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>>
>>     
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>   

-- 
Wei Tai
Student by Research, Knowledge & Data Engineering Research Group
Intelligent Systems Lab
School of Computer Science and Statistics
Trinity College Dublin
Dublin 2
Ireland

> taiw at cs.tcd.ie
> Tel:  +353 (0)1 8968431 