Introduction

Rule-based model is one of most popular paradigm for modeling complex systems, where symbolic, qualitative, relation-based representation of knowledge is necessary. Basically any rule-based system is composed of a set of rules defining its behavior. As a behavior drawing conclusions (or performing actions) based on conditions is meant. Rule-based systems are probably the most popular tools of the AI.

Each rule-based system consists of two parts: rule base and an interpreter, often called an inference engine. The rules define behavior, while the inference engine provides methods to use the rules, takes care about selection and execution. The format of rules is usually defined as follows:

$$IF \; antecendent \; THEN \; consequent$$

and it is considered to be a production rule, in practice equivalent to logical implication (if-then rule)(see also Section 2.3.3).