Re: Announcing syntreenet: A Python library to build scalable production rule systems

Hi,

On Mon, Jul 08, 2019 at 07:47:35AM +0000, fano.ramparany@orange.com wrote:
> Hi,
> 
>  
> 
> I found this interesting slideware : https://ai.ia.agh.edu.pl/wiki/_media/
> en:dydaktyka:krr:rule-based-systems-krakow-2012.pdf which states a relatively
> recent (dated 2012) overview of rule based systems.

Thank you, that is interesting. For a more in depth analysis of forward
chaining RETE based algorithms, Robert Doorenbos' Thesis is quite good.
Nothing fundamental has changed in the field since it was written.

http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf

> 
> To complete some points raised in this thread:
> 
> -          Regarding RETE algorithm, it can be viewed as a compilation of rules
> into a structure stored in the memory, that registers the matching of facts to
> rules conditions as soon as facts or rules are introduced.
> 
> -          Forward chaining (rather than production) is the alternative to
> backward chaining.
> 
>  
> 
> Regards,
> 
> 
> Fano
> 
>  
> 
>  
> 
> De : Amirouche Boubekki [mailto:amirouche.boubekki@gmail.com]
> Envoyé : dimanche 7 juillet 2019 21:48
> À : Enrique Pérez Arnaud
> Cc : Enrique Pérez Arnaud; semantic-web
> Objet : Re: Announcing syntreenet: A Python library to build scalable
> production rule systems
> 
>  
> 
> Like I said, I am very newbie to this kind of algorithms I will need to read
> some stuff about it.
> 
>  
> 
> Seems like Artificial Intelligence: A Modern Approach has a chapter about the
> subject
> 
>  
> 
> Le dim. 7 juil. 2019 à 21:07, Enrique Pérez Arnaud <enrique@cazalla.net> a
> écrit :
> 
>     Hi Amirouche,
> 
>     On Sun, Jul 07, 2019 at 01:02:47PM +0200, Amirouche Boubekki wrote:
>     >
>     > Hello Enrique,
>     >
>     > Thanks for sharing!
> 
>     Thanks for taking interest :)
> 
>     >
>     > Le sam. 6 juil. 2019 à 20:53, Enrique Pérez Arnaud <enrique@cazalla.net>
>     a
>     > écrit :
>     >
>     >     Hi all,
>     >
>     >     Perhaps some of you might be interested in this library I've
>     released, that
>     >     might be used to build production rule systems, with the peculiarity
>     that
>     >     the cost of matching a fact to the knowledge base would be
>     logarithmic in
>     >     the size of said knowledge base, measured as the number of rules plus
>     the
>     >     number of facts in working memory. As far as I know, the current
>     state of
>     >     the art is polynomial.
>     >
>     >     https://gitlab.com/enriquepablo/syntreenet
>     >
>     >
>     >
>     > I am interested in this work. Mind the fact that I am a newbie and I
>     might ask
>     > trivial questions.
>     >
>     > First, I can not tell the importance of this work compared to existing
>     > solutions
>     > even if what is described in the README seems promising.
>     >
>     > Questions:
>     >
>     > A) What about the name syntreenet?
> 
>     "Network of syntagm trees". Just wanted a name that is unique in google.
> 
>     >
>     > B) What are Syntagm?
> 
>     See below
> 
>     >
>     > C) I read the following:
>     >
>     >
>     >     "syntreenet knows nothing about syntax. Facts are a black box with
>     whatever
>     >     internal structure that is appropriate for their universe of
>     discourse.
>     >     syntreenet never composes a fact."
>     >
>     >
>     > What does syntax means in this context?
> 
>     Facts are truths; facts are what we are interested in. And facts might
>     have any internal structure imaginable. They might be triples, for
>     example, as in RDF, or they might be sets of key value pairs, or nested
>     lists, or whatever. I call syntax to that internal structure; syntax is
>     grammar from a different perspective.
> 
>     The point is that there is a universal transformation from facts built
>     with any imaginable grammar (so universal wrt the grammar), to
>     simple trees, and therefore to sets of tuples (the set of paths from
>     each leaf to the root). And those paths carry enough information about
>     the syntactic elements and their position within the facts so as to be used
>     to test whether some other fact matches them.
> 
>     So, what are syntagms? Facts can have any internal structure, but there is
>     a level of detail which must leak to syntreenet, which is the level at
>     which the objects can be logical variables or not. Syntreenet must be
>     able to know whether a given syntactic element in a fact (in one of the
>     paths corresponding to it) is a variable or not.
> 
>     In essence, the question is that in a deduction system we need to manage
>     2 things, facts as carriers of truth and variables as carriers of
>     generalization; and that the way in which the variables are a part of
>     the facts, which depends on the grammar used to buid the facts, is not
>     needed in the deduction procedure, even though within that procedure we
>     need to see the variables within the facts. Using paths is like a
>     universal (grammar independent) way of peeking within the facts to find
>     the variables; a way to isolate the algorithm to make deductions from
>     the internal structure of the deductions.
> 
>     >
>     > It seems to me for the purpose of the demonstration, it would be easier
>     to
>     > avoid to be generic and stick to strings for facts and rules and have a
>     > convention for variables. What do you think?
>     >
>     > Based on this log:
>     >
>     >
>     > adding rule "X1 isa X2; X2 is X3 -> X1 isa X3"
>     > adding rule "X1 is X2; X2 is X3 -> X1 is X3"
>     > adding fact "animal is thing"
>     > adding rule "X1 isa animal -> X1 isa thing"
>     > adding rule "thing is X3 -> animal is X3"
>     > adding rule "X1 is animal -> X1 is thing"
>     >
>     >
>     > It seems like the algorithm rely on pre-computing rules based on existing
>     rules
>     > and facts, isn't it?
> 
>     If you have:
> 
>       X1 isa X2; X2 is X3 -> X1 isa X3
> 
>     And you have:
> 
>       animal is thing
> 
>     then you necessarily have:
> 
>       X1 isa animal -> X1 isa thing
> 
>     So I would not call this pre-computing, perhaps we might call it
>     book-keeping - thinking in the RETE algorithm, which in this situation
>     would not produce a new rule, but keep the match in a beta node. I would
>     just call it logic.
> 
>     > It seems to me the inference process starts before the kb is actually
>     asked
>     > something.
> 
>     This is what production systems are about, in contrast to backward
>     chaining systems.
> 
>     Best!
> 
>     --
>     Enrique Pérez Arnaud
> 
> 
> 
> --
> 
> Amirouche ~ amz3 ~ https://hyper.dev
> 
> _________________________________________________________________________________________________________________________
> 
> Ce message et ses pieces jointes peuvent contenir des informations confidentielles ou privilegiees et ne doivent donc
> pas etre diffuses, exploites ou copies sans autorisation. Si vous avez recu ce message par erreur, veuillez le signaler
> a l'expediteur et le detruire ainsi que les pieces jointes. Les messages electroniques etant susceptibles d'alteration,
> Orange decline toute responsabilite si ce message a ete altere, deforme ou falsifie. Merci.
> 
> This message and its attachments may contain confidential or privileged information that may be protected by law;
> they should not be distributed, used or copied without authorisation.
> If you have received this email in error, please notify the sender and delete this message and its attachments.
> As emails may be altered, Orange is not liable for messages that have been modified, changed or falsified.
> Thank you.
> 

-- 
Enrique Pérez Arnaud