Jess in Action: Java Rule-Based Systems

This book can be used in several ways. First, it is a general introduction to rulebased systems. If you’ve never encountered rule-based systems before, you’ll want to read part 1 closely. This first section of the book introduces the concepts behind rule-based systems, discusses their applications, and shows some first examples of rule-based programs written with Jess. Part 1 also discusses what’s involved in adopting a rule-based solution at your company. Although the programming examples in later chapters use Jess as a vehicle , the concepts presented will transfer to other rule engines easily.

Second, this book is a programmer’s manual for the Jess rule language. Part 2 is part Jess language reference and part tutorial. It first introduces you to the language, and how the language is integrated with Java. Later chapters in this part discuss rules and working memory elements—the data that rules operate on. There’s also a chapter describing some of the theory behind Jess and what makes it run fast.

Part 3 presents an information kiosk, the Tax Forms Advisor, that helps customers choose which income tax forms to bring home. You’ll learn how to collect expert knowledge and condense it into rules. The kiosk as presented has a simple text-based interface.

Part 4 is concerned with the development of the PC Repair Assistant, a helpdesk application with a Swing-based graphical interface. This example builds on and extends some of the software infrastructure developed for the Tax Forms Advisor.

In Part 5, I’ll guide you through the development of the HVAC Controller, an intelligent climate-control system for a hypothetical office building. This part shows how rule-based systems can be interfaced to hardware. A special section written by Bob Orchard, developer of the FuzzyJ toolkit and the FuzzyJess extension for Jess, shows how the HVAC Controller can be enhanced by the use of fuzzy logic.

Part 6 is about web-based e-commerce solutions. This part presents a Recommendations Agent that analyzes a customer’s past and present purchases to recommend additional items of interest. The Recommendations Agent is embedded in a set of servlets and JavaServer Pages in the Tomcat servlet engine.

Part 7 is a little different. The two chapters in this last part cover various topics relevant to using rule-based systems in enterprise applications, including using XML as a rule language, and working with application servers, Enterprise Java Beans, and the J2EE environment.

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