What is Artificial Intelligence?

143 Pages·2016·3.09 MB·English

UNIT I

Overview of A.I: Introduction to AI, Importance of AI, AI and its
related field, AI techniques,Problems, problem space and search:
Defining the problem as a state space search, Productionsystem and
its characteristics, Popular Ai Problems- water Jug Problem,
Missionaries-Cannibal Problem, 8 Puzzle Problem.

A branch of Computer Science named Artificial Intelligence pursues
creating the computers or machines as intelligent as human beings.
What is Artificial Intelligence?
According to the father of Artificial Intelligence, John McCarthy,
itis “The science and engineering of making intelligent machines,
especially intelligent computer programs”.
Artificial Intelligence is a way of making a computer, a computer-
controlled robot, or a software think intelligently, in the similar
manner the intelligent humans think.
AI is accomplished by studying how human brain thinks, and how
humans learn, decide, and work while trying to solve a problem, and
then using the outcomes of this study as a basis of developing
intelligent software and systems.
AI is a study which makes the computers todo things which are, at
the moment, at thehands of human beings.
Views of AI fall into four categories:

 Thinking Humanly(The Cognitive approach)
 Acting Humanly(The Turing Test approach)
 Thinking Rationally(The Laws of Thought approach)
 Acting Rationally(The Rational Agent approach)

Systems that think like humans

―The exciting new effort to make computers think
… machines with minds, in the full and literal
sense.‖(Haugeland,1985)
The cognitive modeling approach

We need to get inside actual working of the human mind :

(a) through introspection – trying to capture our own thoughts as they
go by;
(b) through psychological experiments

Allen Newell and Herbert Simon, who developed GPS,the ―General
Problem Solver tried to trace the reasoning steps to traces of human
subjects solving the same problems The interdisciplinary field of
cognitive science brings together computer models from AI and
experimental techniques from psychology to try to construct precise
and testable theories of the workings of the human mind

Systems that think rationally

―The study of mental faculties through the use of computer models.
(Charniak and McDermont, 1985)

The “laws of thought approach”

The Greek philosopher Aristotle wasone of the first to attempt to
codify ―right thinking that is irrefutable reasoning processes. His
syllogism provided patterns for argument structures that always
yielded correct conclusions when given correct premises—for example,
Socrates is a man; all men are mortal; therefore Socrates is mortal.
These laws of thought were supposed to govern the operation of the
mind; their study initiated a field called logic.

Systems that act like humans

The art of creating machines that performsfunctions that require
intelligence when performed by People. (Kurzweil, 1990)

The Turing Test approach

o Test proposed by Alan Turing in 1950
o The computer is asked questions by a human interrogator.
The computer passes the test if a human interrogator, after posing
some written questions, cannot tell whether the written responses
come from a person or not. Programming a computer to pass, the
computer need to possess the following capabilities:

Natural language processing
to enable it to communicate
successfully in English.

Knowledge representation
to store what it knows or hears

Automated reasoning
to use the stored information to answer
questions and to draw new conclusions.

Machine learning
to adapt to new circumstances and to detect
and extrapolate patterns

To pass the complete Turing Test, the computer will need

 Computer vision to perceive the objects, and
 Robotics to manipulate objects and move about

Systems that act rationally

“Computational intelligence is the studyof the design of intelligent
agents. (Poole et al.,1998)

The rational agent approach

An agent is something that acts. Computer agents are not mere
programs, but they are expected to have the following attributes also:
(a) Operating under autonomous control,
(b) Perceiving their environment,
(c) Persisting over a prolonged time period,
(d) Adapting to change.
A rational agent is one that acts so as to achieve the best outcome.
Philosophy of AI
While exploiting the power of the computer systems, the curiosity of
human, lead him to wonder, “Can a machine think and behave like
humans do?”
Thus, the development of AI started with the intention of creating
similar intelligence in machines that we find and regard high in
humans.
Goals of AI
 To Create Expert Systems − The systems which exhibit intelligent
behavior, learn, demonstrate, explain, and advice its users.
 To Implement Human Intelligence in Machines − Creating systems
that understand, think, learn, and behave like humans.
What Contributes to AI?
Artificial intelligence is a science and technology based on disciplines
such as Computer Science, Biology, Psychology, Linguistics,
Mathematics, and Engineering. A major thrust of AI is in the
development of computer functions associated with human
intelligence, such as reasoning, learning, and problem solving.
Out of the following areas, one or multiple areas can contribute to
build an intelligent system.
Programming Without and With AI
The programming without and with AI is different in following ways −
Programming Without AI Programming With
AI
A computer program without AI can answer A computer program
the specific questions it is meant to solve. with AI can answer
the generic questions
it is meant to solve.
Modification in the program leads to change in its AI programs can
structure. absorb new
modifications by
putting highly
independent pieces of
information together.
Hence you can modify
even a minute piece
of information of
program without
affecting its structure.
Modification is not quick and easy. It may lead to affecting Quick and Easy
the program adversely. program modification.
The domain of artificial intelligence is huge in breadth and width.
While proceeding, we consider the broadly common and prospering
research areas in the domain of AI −
Speech and Voice
Recognition
These both terms are common in robotics, expert systems and
natural language processing. Though these terms are used
interchangeably, their objectives are different.
Speech Recognition Voice Recognition
The speech recognition aims at The objective of voice recognition is to
understanding and comprehending recognize WHO is speaking.
WHAT was spoken.
It is used in hand-free computing, map, It is used to identify a person by
or menu navigation. analyzing its tone, voice pitch, and
accent, etc.
Machine does not need training for This recognition system needs training
Speech Recognition as it is not speaker as it is person oriented.
dependent.
Speaker independent Speech Speaker dependent Speech Recognition
Recognition systems are difficult to systems are comparatively easy to
develop. develop.

Speaker independent Speech Speaker dependent Speech Recognition
Recognition systems are difficult to systems are comparatively easy to
develop. develop.
Working of Speech and Voice Recognition Systems
The user input spoken at a microphone goes to sound card of the
system. The converter turns the analog signal into equivalent digital
signal for the speech processing. The database is used to compare
the sound patterns to recognize the words. Finally, a reverse
feedback is given to the database.
This source-language text becomes input to the Translation Engine,
which converts it to the target language text. They are supported
with interactive GUI, large database of vocabulary, etc.
Real Life Applications of AI Research Areas
There is a large array of applications where AI is serving common
people in their day-to-day lives −
Sr.No. Research Areas Example
1 Expert Systems
Examples − Flight-tracking systems,
Clinical systems.

2 Natural Language Processing
Examples: Google Now feature, speech
recognition, Automatic voice output.
3 Neural Networks
Examples − Pattern recognition systems
such as face recognition, character
recognition, handwriting recognition.

4 Robotics
Examples − Industrial robots for moving,
spraying, painting, precision checking,
drilling, cleaning, coating, carving, etc.

5 Fuzzy Logic Systems
Examples − Consumer electronics,
automobiles, etc.

Task Classification of AI
The domain of AI is classified into Formal tasks, Mundane
tasks, and Expert tasks.
Task Domains of Artificial Intelligence
Mundane (Ordinary) Formal Tasks Expert Tasks
Tasks
Perception
 Mathematics  Engineering
 Geometry  Fault Finding
 Computer Vision
 Logic  Manufacturing
 Speech, Voice
 Integration and  Monitoring
Differentiation
Natural Language Games Scientific Analysis
Processing
 Go
 Understanding
 Chess (Deep Blue)
 Language
 Ckeckers
Generation
 Language
Translation
Common Sense Verification Financial Analysis
Reasoning Theorem Proving Medical Diagnosis
Planing Creativity
Robotics
 Locomotive
Humans learn mundane (ordinary) tasks since their birth. They
learn by perception, speaking, using language, and locomotives. They
learn Formal Tasks and Expert Tasks later, in that order.
For humans, the mundane tasks are easiest to learn. The same was
considered true before trying to implement mundane tasks in
machines. Earlier, all work of AI was concentrated in the mundane
task domain.
Later, it turned out that the machine requires more knowledge,
complex knowledge representation, and complicated algorithms for
handling mundane tasks. This is the reason why AI work is more
prospering in the Expert Tasks domain now, as the expert task
domain needs expert knowledge without common sense, which can
be easier to represent and handle.
What is AI Technique?
Artificial Intelligence research during the last three decades has
concluded that Intelligence requires knowledge. In the real world , to
compensate overwhelming quality, knowledge possesses less
desirable properties.−
 Its volume is huge, next to unimaginable.
 It is not well-organized or well-formatted. It differs from data by being
organized in a way that corresponds to its application
 It keeps changing constantly.
 It is complicated.
 It is difficult to characterize correctly.
AI Technique is a manner to organize and use the knowledge
efficiently in such a way that −