HFE 451/651. Artificial Intelligence and Expert Systems. -Presented By Damodar Kavya Sogra. Contents. Introduction Definitions of AI Approaches of AI History of AI Designing an AI system Applications of AI Expert Systems Conclusion References Questions????. Introduction.
Definitions of AI
Approaches of AI
History of AI
Designing an AI system
Applications of AI
Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent.
AI is a broad topic, consisting of different fields, from machine vision to expert systems. The element that the fields of AI have in common is the creation of machines that can "think".
AI researchers are active in a variety of domains.
Formal Tasks (mathematics, games),
Mundane tasks (perception, robotics, natural language, common sense reasoning)
Expert tasks (financial analysis, medical diagnostics, engineering, scientific analysis, and other areas)
The computer would need to possess
Determine how humans think
Come up with precise theory of the mind and express as a computer program
- Difference between theoretical and practical approach
- More open to scientific development than approaches based on human behavior or thought –clearly defined rationality
The beginnings of AI reach back before electronics, to philosophers and mathematicians such as Boole and others theorizing on principles that were used as the foundation of AI Logic.
AI really began to intrigue researchers with the invention of the computer in 1943
The technology was finally available, or so it seemed, to simulate intelligent behavior
AI has grown from a dozen researchers, to thousands of engineers and specialists; and from programs capable of playing checkers, to systems designed to diagnose disease.
Advanced-level computer languages, as well as computer interfaces and word-processors owe their existence to the research into artificial intelligence.
Top Down Approach
2. Bottom Up Approach
Bottom Up Approach is most widely used
*Logical Operation is based on two or more such signals
- Micro Bankers High Tech Banking System
- Internet Banking
- The Psychotherapist
Expert systems are computerized advisory programs that attempt to imitate the reasoning process and knowledge of experts in solving specific types of problems.
A generalized Interface
Expert systems can do much better
Task involves reasoning and knowledge and not intuition or reflexes
Task can be done in minutes or hours
Task is concrete enough to codify
The task is commonly taught to novice in the area.
Recognized expert exist
There is general agreement among experts
Experts are able and willing to articulate the way they approach problems.
Use AI techniques
Separate knowledge and control
Use inference procedures - heuristics - uncertainty
Model human expert
Conventional System Expert System
Information and processing are Knowledge base is separated from processing combined in one program mechanism
May make mistakes Does not make mistakes
Changes are tedious Changes are easy
System operates only when completed System can operate even with few rules
Data processing is a repetitive process Knowledge engineering is inferential process
Representation and use of data Representation and use of knowledge
They create categories
They use specific rules, a priori rules
They Use Heuristics --- "rules of thumb"
They use past experience --- "cases"
They use "Expectations"
Computer models are based on models of human reasoning
They use rules A--->B--->C
They use cases
They use pattern recognition/expectations
Deal with complex subject which normally require a considerable amount of human expertise.
Exhibit performance and high reliability
Capable of explaining and justifying solutions and recommendations.