I think I am going to try blogging my development progress as a means of providing updates to anyone interested instead of updating this page everytime. The blog can be found
here
This library allows integration and embedding of Jess language scripts into Java JSP
pages, allowing novel ways of embedding AI rule based reasoning into
web based applications. Since the Jess syntax is based on CLIPS and is
used as the Reference Implementation for JSR-94 (Java Rule Engine API),
a wide audience of AI rule-based practioners may find interest and use
in this project. Other examples of working with Jess in a web
environment have focused on embedding the engine into servlets, so the
use of a JSP taglibrary will allow new architectures to be used.
The taglibrary is written Java, and so should be platform independant
insofar as compliant Java JSP/Servlet container isavailable for a
given platform. The taglibrary will actually be based on previous work
I have done in a similar vein, but I never released the source code and
would like to contribute it to the open source community after I have
had a chance to refactor it for the latest developments in the JSP
specification.
Please note that Jess is NOT
distributed under an open
source license, so interested users must obtain an appropriate license
if they wish to use this taglibrary (currently free for academic &
federal work).
I am currently
refactoring and reworking some of my previous work and will make some
early releases available once they get to a base usable state.
The Sourceforge
project page can be located
here
From Jess's home
page:
Jess
is a rule engine and scripting environment written
entirely in Sun's JavaTM
language by Ernest Friedman-Hill at Sandia National
Laboratories in Livermore, CA. Jess was originally
inspired by the CLIPS expert system shell, but has grown into a
complete, distinct, dynamic environment of its own. Using
Jess, you can build Java software that has the capacity
to "reason" using knowledge you supply in the form of declarative
rules. Jess is small, light, and one of the fastest rule
engines available.
Jess can be obtained from
Sandia
National Labs. Users interested in jesstaglib will have to
obtain an appropriate license.