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CHAPTER 1
Introduction
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Introduction
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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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Definition of Artificial Intelligent
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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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Definition of Artificial Intelligent
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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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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 NI enables people to benefit
whereas transferring a body by the use of sensory
of knowledge from one
experience directly, whereas
person to another is a
AI system must work with
lengthy process
symbolic input
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Natural versus AI
Advantages of AI over
Natural Intelligence (NI) :
Advantages of Natural
Intelligence (NI) over AI:
AI can be less expensive
than NI
AI, being computer
technology, is consistent
and thorough whereas NI is
erratic (not consistent)
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
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Natural versus AI
Advantages of AI over
Natural Intelligence (NI) :
Advantages of Natural
Intelligence (NI) over AI:
AI can be documented
The advantages of NI over
whereas natural intelligence AI result in many limitations
is difficult to reproduce
of Expert System
because the person that
makes the decision might
forget at a later date why he
made such decision
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Definition of Expert System
Expert systems
- apply reasoning
capabilities to reach
a conclusion. An
expert system can
process large
amounts of known
information and
provide conclusions
based on them
Case Based Reasoning
- 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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The AI Field
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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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ES Structure
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– Human Expert Problem Solving
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ES Structure
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– Expert System Problem Solving
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ES Characteristic
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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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Conventional versus AI
Conventional Systems
Knowledge and
processing are
combined in one
sequential program
Programs do not make
mistakes (only
programmers do)
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Expert Systems
Knowledge base is
clearly separated from
the processing
(inference) mechanism
(knowledge rules are
separated from the
control)
Program may make
mistakes
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Conventional versus AI
Conventional Systems
Do not usually explain
why input data are
needed or how
conclusions were drawn
The system operates
only when it is
completed
Execution is done on a
step-by-step
(algorithmic) basis
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Expert Systems
Explanation is a part of
most expert systems
The system can operate
with only a few rules (as
a first prototype)
Execution is done by
using heuristics and
logic
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Conventional versus AI
Conventional Systems
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Expert Systems
Needs complete
information to operate
Can operate with
incomplete or uncertain
information
Effective manipulation of
Effective manipulation of
large databases
large knowledge bases
Representation and use of Representation and use of
data
knowledge
Efficiency is a major goal Effectiveness is a major
goal
Easily deals with
Easily deals with
quantitative data
qualitative data
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Tools for Developing ES
Three approaches in building an ES
- languages: use - use a shell
- use an AI
a programming
environment (or
languages
toolkit)
(usually AI
language)
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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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
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- Provides an
interface that
allows the user to
set up reasoning
task and query the
system about its
reasoning strategy
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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 AI languages
Expert
Toolkits
Languages
system
Shells
11%
23%
56%
11%
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