1. CHAPTER 1
Introduction
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2. Introduction
AI is studied in overlapping fields like psychology, neuroscience and engineering, dealing with intelligent behaviour, learning, adaptation and usually developed using customised machines or computers
AI is concerned with producing machines to automate tasks requiring intelligent behaviour
AI means the science and engineering of making intelligent machines, the ability to answer diagnostic and consumer questions, handwriting, natural language and face recognition and so forth.
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3. Definition of Artificial Intelligent
The terms "agent" and "intelligent agent" are ambiguous and have been used in two different, but related senses, which are often confused. In computer science, an intelligent agent (IA) is a software agent that assists users and will act on their behalf, in performing non-repetitive computer-related tasks
In artificial intelligence, the same term is used for intelligent actors, which observe and act upon an environment, to distinguish them from intelligent thinkers isolated from the world
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4. Definition of Artificial Intelligent
An agent in this sense of the word is an entity that is capable of perception and action
Such an agent might be a robot or an embedded real time software system - and is intelligent if it interacts with its environment in a manner that would normally be regarded as intelligent if that interaction were carried out by a human being
An intelligent agent in the first sense might be implemented using conventional software techniques and display no more intelligence than a conventional computer program
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5. Natural versus AI Advantages of AI over Natural Intelligence (NI) :
Advantages of Natural Intelligence (NI) over AI:
AI is permanent whereas NI is perishable
NI is creative, whereas AI is rather uninspired. In AI, tailored knowledge must be built into a carefully constructed system
AI offers ease of duplication whereas transferring a body of knowledge from one person to another is a lengthy process
NI enables people to benefit by the use of sensory experience directly, whereas AI system must work with symbolic input
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6. Natural versus AI Advantages of AI over Natural Intelligence (NI) :
Advantages of Natural Intelligence (NI) over AI:
AI can be less expensive than NI
Perhaps the most importantly, human reasoning is able to make use at all times of a wide context of experience and to deal an individual problem, whereas AI systems typically gain their power by having a very narrow focus
AI, being computer technology, is consistent and thorough whereas NI is erratic (not consistent)
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7. Natural versus AI Advantages of AI over Natural Intelligence (NI) :
Advantages of Natural Intelligence (NI) over AI:
AI can be documented whereas natural intelligence is difficult to reproduce because the person that makes the decision might forget at a later date why he made such decision
The advantages of NI over AI result in many limitations of Expert System
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8. Definition of Expert System
Expert systems
Case Based Reasoning
- apply reasoning capabilities to reach a conclusion. An expert system can process large amounts of known information and provide conclusions based on them
- stores a set of problems and answers in an organized data structure called cases
- system upon being presented with a problem finds a case in its knowledge base that is most closely related to the new problem and presents its solutions as an output with suitable modifications
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9. The AI Field
AI can be classified into several fields according to applied areas of commercial applications such as the following:
Expert System
Natural Language Processing
Speech (Voice) Understanding
Robotics and Sensory Systems
Computer Vision
Intelligent Computer-Aided Instruction (ICAI)
Case-Based Reasoning / Neural Networks
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10. ES Structure
Human Expert Problem Solving
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11. ES Structure
Expert System Problem Solving
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12. ES Characteristic Mainly include:
Neural networks: systems with very strong pattern recognition capabilities
Fuzzy systems: techniques for reasoning under uncertainty, have been widely used in modern industrial and consumer product control systems
Evolutionary computation: applies biologically inspired concepts such as populations, mutation and survival of the fittest to generate increasingly better solutions to the problem
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13. Conventional versus AI
Conventional Systems
Expert Systems
Knowledge and processing are combined in one sequential program
Knowledge base is clearly separated from the processing (inference) mechanism (knowledge rules are separated from the control)
Programs do not make mistakes (only programmers do)
Program may make mistakes
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14. Conventional versus AI
Conventional Systems
Expert Systems
Do not usually explain why input data are needed or how conclusions were drawn
Explanation is a part of most expert systems
The system operates only when it is completed
The system can operate with only a few rules (as a first prototype)
Execution is done on a step-by-step (algorithmic) basis
Execution is done by using heuristics and logic
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15. Conventional versus AI
Conventional Systems
Expert Systems
Needs complete information to operate
Can operate with incomplete or uncertain information
Effective manipulation of large databases
Effective manipulation of large knowledge bases
Representation and use of data
Representation and use of knowledge
Efficiency is a major goal
Effectiveness is a major goal
Easily deals with quantitative data
Easily deals with qualitative data
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16. Tools for Developing ES
Three approaches in building an ES
- languages: use a programming languages (usually AI language)
- use a shell
- use an AI environment (or toolkit)
1. Languages
ES may be written in symbolic languages, e.g. LISP,  or PROLOG or in conventional high level languages such as FORTRAN, C and PASCAL
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17. Tools for Developing ES
2. Expert System Shells - A shell is a program that can be used to build expert systems.
ES shell performs three major functions
- Assists in building the knowledge base by allowing the developer to insert knowledge into knowledge representation structures
- Provides methods of inference or deduction that reason on the basis of information in the knowledge base and new facts input by the user
- Provides an interface that allows the user to set up reasoning task and query the system about its reasoning strategy
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18. Tools for Developing ES
3. AI Environments or Toolkits
More expensive & powerful than languages or shells
Advantage of using toolkits:
They provide a variety of knowledge representation techniques such as rules and frames (inheritance)
The actual figures for different development tools used by expert system builders in the UK
Conventional Languages
AI languages
Expert system Shells  
Toolkits
11%
23%
56%
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