Artificial Intelligence and expert syste

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Artificial Intelligence and Expert Systems : 

Artificial Intelligence and Expert Systems Presented by:Ms. Smriti Tiwari, Lecturer,MCA Medicaps Institute of Techno-Management,Indore

Why do AI? : 

Why do AI? Two main goals of AI: To understand human intelligence better. We test theories of human intelligence by writing programs which emulate it. To create useful “smart” programs able to do tasks that would normally require a human expert.

Who started AI?The founding Father of AI : 

Who started AI?The founding Father of AI Other names to remember: Minsky Papert Holland De Garis Moravec Brooks

What is AI? : 

What is AI?

How do we classify research as AI? : 

How do we classify research as AI?

What is Intelligence? : 

What is Intelligence? The ability to learn and to cope. The ability to contemplate, think, and reason.

Artificial Intelligence: definitions : 

Artificial Intelligence: definitions

What are the objectives of Artificial Intelligence? : 

What are the objectives of Artificial Intelligence?

What AI is not. : 

What AI is not. AI is not the study and creation of conventional computers systems. Even though one can argue that all programs exhibit some degree of intelligence an AI program will go beyond this in demonstrating a high level of intelligence required of human in performing some task. AI is not the study of mind nor of the body nor of languages as customarily found in the fields of psychology ,physiology, cognitive science or linguistics.

Slide 10: 

But in AI the goal is to develop working computer systems that are truly capable of performing tasks that require high levels of intelligence. The imp point is that the systems all be capable of performing intelligent tasks effectively and efficiently.

Major Branches of AI : 

Major Branches of AI Perceptive system A system that approximates the way a human sees, hears, and feels objects Vision system Capture, store, and manipulate visual images and pictures Robotics Mechanical and computer devices that perform tedious tasks with high precision Expert system Stores knowledge and makes inferences

Slide 12: 

Learning system Computer changes how it functions or reacts to situations based on feedback Natural language processing Computers understand and react to statements and commands made in a “natural” language, such as English Neural network Computer system that can act like or simulate the functioning of the human brain

Slide 14: 

In the area of robotics, computers are now widely used in assembly plants, but they are capable only of very limited tasks. Robots have great difficulty identifying objects based on appearance or feel, and they still move and handle objects clumsily.

Slide 15: 

Natural-language processing offers the greatest potential rewards because it would allow people to interact with computers without needing any specialized knowledge. You could simply walk up to a computer and talk to it. Unfortunately, programming computers to understand natural languages has proved to be more difficult than originally thought. Some rudimentary translation systems that translate from one human language to another are in existence, but they are not nearly as good as human translators.

Slide 16: 

There are also voice recognition systems that can convert spoken sounds into written words, but they do not understand what they are writing; they simply take dictation. Even these systems are quite limited -- you must speak slowly and distinctly.

Slide 17: 

In the early 1980s, expert systems were believed to represent the future of artificial intelligence and of computers in general. To date, however, they have not lived up to expectations. Many expert systems help human experts in such fields as medicine and engineering, but they are very expensive to produce and are helpful only in special situations.

Slide 18: 

There are several programming languages that are known as AI languages because they are used almost exclusively for AI applications. The two most common are LISP and Prolog.

Expert Systems : 

Expert Systems

Objective of an expert system : 

Objective of an expert system To transfer expertise from human experts to a computer system and Then on to other humans (non-experts) It is called a system because it contains three basic components: 1. a knowledge base of facts 2. rules about the domain, or area of expertise 3. a reasoning or “inferencing” mechanism with a user interface

Slide 21: 

Expertsystem Domain expert Knowledge engineer Knowledge user

Participants in Expert Systems Development and Use : 

Participants in Expert Systems Development and Use Domain expert The individual or group whose expertise and knowledge is captured for use in an expert system Knowledge user The individual or group who uses and benefits from the expert system Knowledge engineer Someone trained or experienced in the design, development, implementation, and maintenance of an expert system Schematic

Overview of Expert Systems : 

Overview of Expert Systems Explain their reasoning or suggested decisions Display intelligent behavior Draw conclusions from complex relationships Provide portable knowledge Expert system shell A collection of software packages and tools used to develop expert systems

Slide 24: 

Inferenceengine Explanationfacility Knowledgebaseacquisitionfacility Userinterface Knowledgebase Experts User Architecture of Expert System

Explanation Facility : 

Explanation Facility A part of the expert system that allows a user or decision maker to understand how the expert system arrived at certain conclusions or results

Knowledge Acquisition Facility : 

Knowledge Acquisition Facility Provides a convenient and efficient means of capturing and storing all components of the knowledge base Knowledgebase Knowledgeacquisitionfacility Joe Expert

Expert Systems Development : 

Determining requirements Identifying experts Construct expert system components Implementing results Maintaining and reviewing system Expert Systems Development Domain The area of knowledgeaddressed by theexpert system.

Advantages of Expert Systems : 

Advantages of Expert Systems One can view entire resoning process Easy to develop and modify Development by knowledge engineers and users It acts as a good problem solver and tutor

Limitations of Expert Systems : 

Limitations of Expert Systems Not widely used or tested Limited to relatively narrow problems Cannot readily deal with “mixed” knowledge Possibility of error Cannot refine own knowledge base Difficult to maintain May have high development costs Raise legal and ethical concerns

Applications of Expert Systems and Artificial Intelligence : 

Applications of Expert Systems and Artificial Intelligence Credit granting Information management and retrieval AI and expert systems embedded in products Plant layout Hospitals and medical facilities Help desks and assistance Employee performance evaluation Loan analysis Virus detection Repair and maintenance Shipping Marketing Warehouse optimization



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