Components of ES-1

Today we continue our talk on ES components.
(a) Knowledge based : The knowledge base contains both facts that describe the problem area and knowledge representation techniques that describe how the facts fits together in a logical manner. The term problem domain is used to describe the problem area. The popular knowledge representation techniques are rules and networks of rules.

The rules in the knowledge base are usually coded in the form. IF X THEN Y, where X is a condition, Y is an action to be taken if the condition is true. All the rules contained in an expert system are called the rule set.

The rules of a rule set are not physically linked, but their logical relationships can be established.

(b) Inference engine : The inference engine is the portion of the expert system that performs reasoning by using the contents of the knowledge base in a particular sequence. During the consultation, the inference engine examines the rules of the knowledge base one at a time, and when a rule’s condition is true, specified action is taken. In expert system terminology, the rule is fired when the action is taken.

Components of ES

Expert system consists of 4 major parts
1. user interface
2. knowledge base
3. inference engine
4. development engine

(a) Interface: The user interface enables the user to enter instructions & information into the expert system and also to receive information from it. The instructions specify the parameters that guide the expert system through its reasoning process. The information is in the form of value assigned to certain values. For example. For online blinds store, they ask which product they want- vertical blinds or roman shades, which size they want etc. Another example is Instant Life Insurance Rates company, who are providing Life Insurance Quotes online, they ask their customer to enter their certain details when they are applying for term life insurance.

1. Expert system inputs: The user can use 4 methods for input purposes : menus, commands, natural language and customized interfaces.

2. Expert system outputs : Expert systems are designed to recommend solutions. These solutions are supplemented by explanations. There are two types of explanations : Explanation of questions and Explanation of problem solution.

i) Explanation of questions: The manager may desire explanations while the expert system performs its reasoning. Perhaps the expert system will prompt the manager to enter some information. The manager asks why the information is needed, and the expert system provides an explanation.
ii) Explanation of problem solution: After the export system provides a problem solution, the manager can ask for an explanation of how it was reached. The expert will display each of the reasoning steps leading to the solution.

Expert system (ES)

An expert system is a computer application that guides the performance of ill structured tasks, which usually require experience and expertise. Using an expert system, a non expert can achieve performance, which is comparable to an experts performance in that particular domain.

An expert system is very similar to a decision support system, ie; both are intended to provide a high level of problem solving support to their users. But they differ in two major ways:

First, a DSS consists of routines that reflect as to how the manager believes a problem should be solved, as well as the manager’s style and capabilities. An expert system on the other hand, offers the opportunity to make decisions that exceed the manager’s capabilities.

The second but most important difference between DSS and Es is the ability of the expert system (ES) to explain its line of reasoning in reaching a particular solution. Very often, the explanation of how a solution was reached is more valuable than the solution itself.

Knowledge based Systems-1

We are going to discuss on each component today.
1. Expert Systems: It is a computer program that attempts to represent the knowledge of human experts in the form of heuristics.

2. Robotics: They consist of computer controlled devices that help in AI applications.

3. Natural Language: This enables users to communicate with the computer in different languages and also enables the computer to check grammar and spellings.

4. Learning: This encompasses all the activity that enables the computer or other device to acquire knowledge in addition to what has been entered into the memory by its manufacturers and programmers.

5. Computer vision: This is to endow computers with the ability to recognize and identify objects and the context to which they belong. This also entails an ability to recognize shapes, features etc. automatically and in turn automate movement through robots.

6. Perceptive Systems: These use visual images and auditory signals to instruct computers or other devices such as robots.

7. Artificial intelligence hardware: This includes physical devices that help in artificial intelligence applications. Examples are hardware that is dedicated to knowledge based systems, neural computers used to speed up calculations etc.

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Knowledge based Systems

We going to discuss on knowledge based system like artificial intelligence, expert systems, neural network, robotics etc. At the end of this topic, reader will be in a position for successful expert system development.

Artificial Intelligence (AI)
Artificial intelligence can be defined as a field of study that designs and develops machines capable of performing tasks that would require intelligence if performed by a human being.

A more formal definition of artificial intelligence is that, it is a branch of computer science concerned with designing intelligent computer systems, ie; systems that exhibit the characteristics associated with intelligence in human behavior – understanding, language, learning, reasoning etc.

Components of AI
Broadly speaking, AI consists of
1. Expert systems
2. Robotics
3. Natural Language
4. Learning
5. Computer Vision
6. Perceptive Systems
7. Artificial Intelligence hardware
8. Neural Networks

We will discuss on each component in our next post.