[comp.ai.digest] boolean reasoning

zepp@duttnph.UUCP (Frank Zeppenfeldt) (08/01/88)

Organisation: University of Technology, Delft  The Netherlands.
Date: Thu, 28 Jul 88 10:47 EDT
From: Frank Zeppenfeldt <mcvax!duttnph!zepp@uunet.UU.NET>
To: AILIST@AI.AI.MIT.EDU
Subject: boolean reasoning 

I'm a graduate student and currently looking into some problems 
concerning  low-level and boolean reasoning for (real-time) process 
control. Till now the only literature I could find on this topic has
been the article :

  Logical Controls via Boolean Rule Matrix Transformations
  By : Carl G.Looney and Abdulrudah A.Alfize
  IEEE Trans. on Systems, Man and Cybernetics ,
  Vol SMC-17 no.6 Nov/Dec 1987

It describes how from an initial state of a truth-vector all the
possible truths can be deduced in one step, given a matrix  which
represents the rules. This is done via the transitive closure of
the graph that is represented by the matrix.

Example 1 : initial rulebase 	a --> b  /* a,b and c are boolean */
				b --> c  /* or 8 bits values */
	    becomes after computing the transitive closure ,
				a --> b  /* still the same */
				b --> c	 /* idem */
				a --> c  /* new ! */

In this case, some matrix multiplications are sufficient.
Now suppose we have , 	 a + b  --> c
      			 ac + d --> e,
things are getting more complex to express the LHS of e in terms of
a,b and d. The reason for determining the transitive closure of the 
rulebase is the fact that I want to load these rules in their 
Conjunctive Normal Format in a logic array and apply them in 
parallel. Every use of some RHS result in a LHS of a rule will
generate a recursive entry. I want to avoid that in hardware.
My prolog solution is of complexity  O(#rules^4) ! .

My questions :
1.	The E-mail addresses of Mr. Looney or Mr.Alfize at
	the University of Nevada.
2.	Does somebody know about algorithms to compute the transi-
	tive closure of such a rulebase or AND/OR graph (using the
	available boolean instructions on microprocessors) ?
3.	Is there anyone who can give me examples or references
	using this kind of parallel production systems or low-
	level reasoning ? 

I thank you in advance for any reactions,

	Frank Zeppenfeldt  ..mcvax!dutrun!duttnph!zepp	
	University of Technology Delft
	Department of Applied Physics
	Pattern Recognition Group
	Lorentzweg 1 
	2628 CJ Delft
	The Netherlands.