Rule-Based System

1. What is a rule-based system?‍

A rule-based system is a system that's applied on semi-synthetic rules to store and manipulate information. In doing so, it tries to repeat human intelligence. In terms of working, rule-based systems need a collection of facts or a supply of knowledge and a collection of rules for manipulating that information. These rules are typically named as ‘If statements’ as they have a tendency to usually follow the logic of ‘IF X happens THEN do Y’.r Check

2. What are rule-based systems also known as?‍

Rule-based systems are also known as production systems or expert systems.

3. What are the types of rule-based systems?‍

There seem to be four different ways people think about and want to use rules:

• Derivation or Deduction Rules: These are CWM's normal rules. Each rule expresses the knowledge that if one set of statements happens to be true, then some other set of statements must also be true. In most cases, this is the same as what is sometimes called a logical implication, a material conditional, or a Horn clause.
  

• Transformation Rules: These are what CWM uses with filters. Each rule relates the truth in one database to the truth in another. Transformation rules on n-tuples can be rewritten as derivation rules on (n+1)-tuples, where the additional element specifies the knowledge base.
  

• Integrity Constraints: These are rules of the form "it must be true that ....". CWM does not have these rules, but they can be emulated with derivation rules like "if it is not true that .... then we-have-an-error" and then check for "we-have-an-error".
  

• Reaction or Event-Condition-Action (ECA) Rules: These involve a notion of action and not just inference when a rule applies. Reaction rules may be emulated by wrapping a reaction rule system in a procedure in which queries can be raised for the actions to be performed.

4. What are the types of rule-based engines?

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a. Automated Theorem Provers.

Automated reasoning using first-order became generally feasible in 1965 with Robinson's resolution and hyper resolution algorithms. Today a ton of automated theorem provers continue this tradition, but they see little use of it in general computing. The strength here is general expressive power - the machine performs classical logic operations; the weakness here is that such systems generally are too practical, causing real-world application problems.\\

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b. Logic Programming.‍

In 1970-1972, Prolog introduced Logic Programming, which took a restricted form of first-order logic (Horn clauses) and offered to prove things with them in a deterministic order, very much like running a program. Prolog always chains backward from a query.

c. Production Systems.‍

Production systems present rules as being "triggered" and causing actions.

d. Modern Reasoners.

Modern reasoners and rule systems often use a complex hybrid of strategies or are simply developed for a focussed application domain.

5. What is a rule-based language?‍

In a rule-based language, programs consist of a set of rules. Each rule has two parts, called the head that represents the consequences and the body that represents premises, respectively. A rule-based system attempts to derive execution instructions from a starting set of data and rules.

6. What is a rule-based classifier?‍

Rule-based classifiers are just another type of classifiers that make the class decision depending on using various “if /then” rules. These rules are easily interpretable and thus these classifiers are generally used to generate descriptive models. The condition used with “if” is called the antecedent and the predicted class of each rule is called the consequent.

7. What are the properties of a rule-based classifier?‍

Properties of rule-based classifiers:

• Coverage: The percentage of records that satisfy the antecedent conditions of a particular rule.
• The rules generated by the rule-based classifiers are generally not mutually exclusive, i.e. many rules can cover the same record.
• The rules generated by the rule-based classifiers may not be exhaustive, i.e. there may be some records that are not covered by any of the rules.
• The decision boundaries created by them are linear, but these can be much more complex than a decision tree because many rules are triggered for the same record.

8. What is a fuzzy rule-based system?‍

Fuzzy rule-based systems are rule-based systems, where fuzzy sets and fuzzy logic are used as tools for representing different forms of knowledge about the problem at hand, as well as for modeling the interactions and relationships existing between its variables.