Knowledge Based Systems

Topics: Artificial intelligence, Expert system, Knowledge engineering Pages: 5 (1119 words) Published: November 27, 2012
What is a knowledge-based system?
A system which is built around a knowledge base. i.e. a collection of knowledge, taken from a human, and stored in such a way that the system can reason with it. Example:
System: What is the patient's name?
User: George Smith
System: What is the patient's age?
User: 52 years
System: Is the patient male or female?
User: Male
System: What are the symptoms?
User: Headache dizziness upset stomach high fever
System: When did these symptoms first appear?
User: 23/03/2002
System: I conclude that the patient has a viral infection , my recommendation is that he should take two aspirin, drink plenty of fluid, get lots of rest.

What is knowledge?
Knowledge is the sort of information that people use to solve problems. Knowledge includes facts, concepts, procedures, models, heuristics, etc. Knowledge may be:
* specific or general
* exact or fuzzy
* procedural or declarative

What is an expert system?
* A particular kind of knowledge-based system
* One in which the knowledge, stored in the knowledge base, has been taken from an expert in some particular field. Therefore, an expert system can, to a certain extent, act as a substitute for the expert from whom the knowledge was taken. What is Artificial Intelligence?

Artificial Intelligence (AI) is concerned with exploring such aspects of human (and other animal) mental activity as: * understanding
* creativity
* Perception
* problem-solving
* consciousness
* using language
* Intelligence by simulating them using computers.
It is therefore closely connected with such social sciences as: * psychology
* linguistics
* philosophy
Applied Artificial Intelligence
What is applied AI?
Applied AI is concerned with producing software which is “intelligent” It is intelligent in that it is based on what we know about human reasoning and other mental abilities We are therefore talking about a branch of advanced computing - computer technology - rather than social science Knowledge engineering

The term “knowledge engineering” is often used to mean the process of designing, building and installing an expert system or other knowledge-based system. Some authors use the term to mean just the knowledge acquisition phase. Experts

An expert is an experienced practitioner in his/her particular field. More than that, he/she is a highly effective problem-solver and decision-taker in that field. Experts have three qualities:
* They make good decisions
* They make those decisions quickly
* They are able to cope with a wide range of problems.
Experts and expert systems
Note that:
The task that an expert system performs will generally be regarded as difficult. An expert system almost always operates in a rather narrow field of knowledge. The field of knowledge is called the knowledge domain of the system. There are many fields where expert systems can usefully be built. There are also many fields where they can’t. Note also that an expert can usually explain and justify his/her decisions.

Reasons for building an E.S.
One might build an expert system for any or all of the following reasons: * To archive an expert’s knowledge, to insure against the day when he/she leaves, or retires, or dies. * To disseminate his/her knowledge, so that it is available in more (possibly many more) places than the location of the expert. * To ensure uniformity of advice/decisions.

* As a basis for training other specialists.
Advantages of expert systems
E.S. have the following advantages over human experts:
* The knowledge is permanent
* The knowledge is easily replicated
* The knowledge is represented explicitly, and can be evaluated * The system is consistent - whereas human practitioners have bad days, computers don’t. * Once built, running costs are low

Disadvantages of expert systems
a) Developing an expert system usually costs a great deal of time...
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