Dear Eric,
unfortunately, I can't give you any specific answer on algorithms such
as Guassian elimination. Nevertheless, here are a few pointers you
might be interested in.
You may be interested in the XRI (eXtended Real Interval) extension to
Mozart.
On 16.02.2005, at 15:38, Gustavo Gutierrez Sabogal wrote:
Hi Carlos,
Hello. I'm new in mozart.
I'm trying to solve a problem which implies real numbers. When I
import
the RI module as the documentation says, I get an error of non
existence
of the module. I have searched the module into the mozart directory
installation without success. Can it be downloaded?. From where?. Any
advice about using that module?.
Thanks.
The real interval module from mozart contribs is not working as far as
i know. It works fine with mozart 1.2.5 and linux. Portability of
programs
using this module is not possible. Here in Colombia we have developed a
new more portable real interval constraint system for mozart called XRI
which stands for eXtended Real Interval. This module has been ported to
other platforms different from linux: MacOs X (powerpc) and Windows. If
you wish to try it, go to http://home.gna.org/xrilpoz/
Please, don't hesitate to ask for help or to share your experience for
feedback.
All the best,
Gustavo Gutierrez
The book by Christian:
@Book{Schulte:Book:2002,
Author = "Christian Schulte",
Title = "Programming Constraint Services",
Publisher = "Springer-Verlag",
Year = 2002,
Address = "Berlin, Germany",
Series = "Lecture Notes in Artificial Intelligence",
Volume = 2302,
OPTURL =
"http://link.springer.de/link/service/series/0558/tocs/t2302.htm";,
Abstract = "
Constraint programming is an approach to modeling and solving
combinatorial
problems that has proven succesful in many applications. Building on
techniques developed in AI, logic programming and operations research,
constraint programming is based on an abstraction that decomposes the
problem solver into a reusable constraint engine and a declarative
program modeling the problem.
This book is concerned with the architecture and implementation of
constraint
engines. The author's main contribution is that constraint services,
such as search and combinators, are made programmable; this is
achieved
by devising computation spaces as simple abstraction for programming
constraint services at a high level. State-of-the-art and novel search
strategies, such as visual interactive search and parallel search
are covered.
The book is indispensible reading for anyone seriously interested in
constraint technology."
}
Furthermore, there is the C++ lib Gecode which promises to make the
definition of new domains more easy.
GECODE: www.gecode.org
On 27.10.2005, at 12:44, Christian Schulte wrote:
Are there perhaps any plans to integrate Gecode in Mozart as well?
I don't know whether there are any plans. Maybe the only thing that I
can
(have to) say is that it is easy enough to do. We are currently
focusing on
having a release out in November and then have a good Java interface
out
soon after that.
Best,
Torsten
On 10.01.2006, at 20:17, [EMAIL PROTECTED] wrote:
I have a really tangential question, and I hope it's not too far off
topic. :-/
I've recently run into some constraint problems. For example, I need
to
solve systems of linear equations over real numbers, and perhaps
generalize this in various directions. I understand how to propagate
these constraints using well-known algorithms. But I'm looking for a
language which makes this style of programming natural.
Everything I've read suggests that CLP is a promising technique:
There's
a whole family of research languages from CLP(R) onward which tackle
constraint problems in elegant ways.
But here's where I get stuck: The most popular constraint
languages--Oz,
Alice, GNU Prolog, etc.--focus heavily on finite domains. In some
cases, a real-interval library is available. What I want, though, is
strong propagators: Guassian elimination, the simplex method, and other
tools of that sort. And I don't understand how to make the jump from
finite
domains to these tools.
I've read CTM chapter 12 (what a cool book!), and I understand how a
language like CLP(R) fits together. I even see some analogies between
CLP(R)'s deferred constraints and a dataflow model. But I don't know
how to reimplement these tools in Mozart.
So, my questions:
1) Can propagation algorithms such as Guassian elimination be
represented elegantly using Mozart?
2) If so, what papers, books or code do I need to read to get
unstuck?
Thank you for any advice you can provide!
Sincerely,
Eric
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Torsten Anders
Sonic Arts Research Centre
Queen's University Belfast (UK)
www.torsten-anders.de
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