Chapter 12 provides an overview of artificially intelligent decision support systems. It examines major branches of study in the AI field and how each may contribute to injecting artificially intelligent behavior into DSSs. It traces the history of technological advances leading to a class of artificially intelligent DSSs known as expert systems. The potential benefits of these systems to individuals and organizations are examined.

Chapter 13 concentrates on how to represent reasoning knowledge as rules and how to process those representations. Two of the most prominent processing methods are forward chaining and backward chaining. These are alternative approaches for using a set of rules to draw inferences about the values of variables. Both of these inference methods are considered in detail.

Chapter 14 is concerned with developing rule-based decision support systems. There are some important aspects to this expert system development that differ from conventional DSS development. One of these involves the acquisition of reasoning knowledge for incorporation into a knowledge system. Both the context and process of knowledge acquisition are considered. These fit within a 7-step development cycle for building expert systems.

Chapter 15 presents a variety of advanced topics related to reasoning with rules: how rigorous the inference will be, in what order rules will be selected for processing, what strategy will guide the evaluation of a rule's premise, and the timing of when inference will happen. The incorporation of uncertainty into reasoning and the treatment of fuzzy (multivalued) variables are also examined.