JSP Taglibrary for Jess

Dev Blog

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.

Project Page

The Sourceforge project page can be located here

About Jess

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.

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