CHAPTER
1
Introduction to
Artificial Intelligence
1.1. INTRODUCTION
Artificial Intelligence is a branch of computer science dealing with develop computers
behave similar to human being. Major AI textbooks define artificial intelligence as “study
and development of intelligent agents,” where an intelligent agent is a computer based
system that analyses its environment and takes actions which maximize its chances of success.
John McCarthy, who first time give name the term in 1956, defines it as “the mythology of
making intelligent machines, especially intelligent computer programs.”
According to many researchers and different AI Text Books the definitions of AI are
categorized into four approaches given below:
1. Systems that think like humans: Creation a computer system that can think like
human being, in other words we can say that it pass Turing test. Turing test is proposed by
Alan Turing in 1950 to check machine is intelligent or not. Program a computer to pass
Turing test, the computer need to possess the following capabilities :
(a) Natural language processing: Make a computer so powerful so that it can
communicate in natural language like English.
(b) Knowledge representation: Computer should store its observation for future use.
(c) Automated reasoning: Computer can use its stored knowledge to taking action
and formulate new conclusion.
(d) Machine learning: Computer can learn from experience and adjust itself into new
situations.
(e) Computer vision: Computer can perceive the objects, and identify each object.
(f) Robotics: It can use objects according to situation.
2. Systems that can think rationally: “The study of human brain through the use of
computer models.” (Charniak and McDermont, 1985).We need to get inside actual working
of the human mind.
3. Systems that act like humans: “The art of Developing machines that can perform
task require intelligence when performed by people.”
4. Systems that act rationally: Develop intelligent agent that can perform task like
human. Computer agents are not mere programs, but they are expected to have the following
attributes also:
(a) It should be autonomous control.
,1.2 INTRODUCTION TO ARTIFICIAL INTELLIGENCE
(b) Understand its environment using sensor.
(c) Persisting over a prolonged time period.
(d) It can adjust itself in new environment.
1.2. FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
1.2.1. Turing Test
Alan Turing [1950] developed an empirical test of artificial intelligence, The Turing
test is an operational test; that is, it provides a concrete way to determine whether the entity
is intelligent. The test involves a human interrogator who is in one room, another human
being in second room, and an artificial entity in a third room. The interrogator is allowed to
communicate with both the other human and the artificial entity only with a textual device
such as a terminal. The interrogator is asked to distinguish the other human from the artificial
entity based on answers to questions posed by the interrogator. If the interrogator cannot do
this, the Turing test is passed and we say that the artificial entity is intelligent. The computer
is interrogated by a human via a teletype. It passes if the human cannot decide what is at the
other end a computer or human.
Human? Human?
Machine? Machine?
Room A Room B
Room C
Human Interrogator
Fig. 1.1. Pictorial Representation of Turing Test
1.2.2. Chinese room Experiment
Searle [1980] took exception to the Turing test with his Chinese room thought
experiment. The experiment proceeds as follows: Suppose that we have successfully
developed a computer program that appears to understand Chinese. That is, the program
takes sentences written with Chinese characters as input, processes the characters, and outputs
sentences written using Chinese characters. If it is able to convince a Chinese interrogator
that it is a human, then the Turing test would be passed. Searle asks “does the program
literally understand Chinese or is it only simulating the ability to understand Chinese?” To
address this question, Searle proposes that he could sit in a closed room holding a book
containing English translation of the program, and adequate paper and pencils to carry out
the instructions of the program by hand. The Chinese interrogator could then provide Chinese
sentences through a slot in the door, Searle could process them using the program’s
instructions, and send Chinese sentences back through the same slot. Searle says that he has
performed the exact same task as the computer that passed the Turing test. That is, each is
following a program that simulates intelligent behavior. However, Searle notes that he does
not speak Chinese. Therefore, since he does not understand Chinese, the reasonable
conclusion is that the computer does not understand Chinese either. Searle argues that if the
computer does not understand the conversation, then it is not thinking, and therefore it does
not have an intelligent mind. Searle formulated the philosophical position known as strong
AI, which is as follows: The accurately programmed computer has mind, meaning that
, INTRODUCTION TO ARTIFICIAL INTELLIGENCE 1.3
computers can understand programs if they are correctly written in a language. Based on his
Chinese room experiment, Searle concludes that strong AI is not possible. Searle’s paper
resulted in a great deal of controversy and discussion for some time to come. The position
that computers could appear and behave intelligently, but not necessarily understand, is
called weak AI. The essence of the matter is whether a computer could actually have a mind
(strong AI) or could only simulate a mind (weak AI).
1.3. THE HISTORY OF ARTIFICIAL INTELLIGENCE
1. The Thinking of Artificial Intelligence (1943-1955)
There are number of examples available in past which can be related to that kind of
work which belongs to AI category, but Alan Turing is known as first person who first think
a complete vision of AI in his 1950 article “Computing Machinery and Intelligence.” In
it, he define the Turing test, machine learning, genetic algorithms, and reinforcement learning.
2. The Birth of Artificial Intelligence (1956)
In 1956 McCarthy meet to Minsk, Claude Shannon, and Nathaniel Rochester and make
a team together for research purpose. Claude Shannon and Nathaniel Rochester are U.S.
researchers expert in automata theory, neural network, and artificial intelligence. They all
together organized a two-month workshop at Dartmouth in the summer of 1956. The most
important achievement of this workshop is the agreement to adopt McCarthy’s suggested
new name to this field called artificial intelligence.
3. Early Journey of Artificial Intelligence (1952-1969)
Many researchers devote their time to increase the field of artificial intelligence.
4. General Problem Solver (GPS)
GPS was a computer program Developed in 1957 by Herbert Simon and Allen Newell for
development of universal problem solver machine. This program was a first program that thinks
somehow like human think. Herbert Gelernter developed a Geometry Theorem Solver, which
can be used to solve theorem quickly. Lisp was invented by John McCarthy in 1958 while he was
at the Massachusetts Institute of Technology. In 1963, McCarthy started the AI lab at Stanford.
5. Generation of Knowledge Based Systems (1966-1973)
During this span of time there are two most important knowledge based system was
introduced they are Dendral, and computer software expert system. Today an expert system
is a popular system for doing expert tasks.
6. AI Becomes an Industry (1980-present)
There are many project started in this age for example Japan started a project to built a
computer that can run on Prolog.
7. The Return of Neural Networks (1986-present)
Neural network is introduced in this period which become a powerfully tool in learning
today. This is used to increase the efficiency of system like fingerprint recognition system.
8. Hidden Markov Model and Bayesian Network (1987-present)
Hidden Markov model and Bayesian network introduced in this age. Today hidden
Markov models (HMMs) is become a tool for prediction. We are using various applications
1
Introduction to
Artificial Intelligence
1.1. INTRODUCTION
Artificial Intelligence is a branch of computer science dealing with develop computers
behave similar to human being. Major AI textbooks define artificial intelligence as “study
and development of intelligent agents,” where an intelligent agent is a computer based
system that analyses its environment and takes actions which maximize its chances of success.
John McCarthy, who first time give name the term in 1956, defines it as “the mythology of
making intelligent machines, especially intelligent computer programs.”
According to many researchers and different AI Text Books the definitions of AI are
categorized into four approaches given below:
1. Systems that think like humans: Creation a computer system that can think like
human being, in other words we can say that it pass Turing test. Turing test is proposed by
Alan Turing in 1950 to check machine is intelligent or not. Program a computer to pass
Turing test, the computer need to possess the following capabilities :
(a) Natural language processing: Make a computer so powerful so that it can
communicate in natural language like English.
(b) Knowledge representation: Computer should store its observation for future use.
(c) Automated reasoning: Computer can use its stored knowledge to taking action
and formulate new conclusion.
(d) Machine learning: Computer can learn from experience and adjust itself into new
situations.
(e) Computer vision: Computer can perceive the objects, and identify each object.
(f) Robotics: It can use objects according to situation.
2. Systems that can think rationally: “The study of human brain through the use of
computer models.” (Charniak and McDermont, 1985).We need to get inside actual working
of the human mind.
3. Systems that act like humans: “The art of Developing machines that can perform
task require intelligence when performed by people.”
4. Systems that act rationally: Develop intelligent agent that can perform task like
human. Computer agents are not mere programs, but they are expected to have the following
attributes also:
(a) It should be autonomous control.
,1.2 INTRODUCTION TO ARTIFICIAL INTELLIGENCE
(b) Understand its environment using sensor.
(c) Persisting over a prolonged time period.
(d) It can adjust itself in new environment.
1.2. FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
1.2.1. Turing Test
Alan Turing [1950] developed an empirical test of artificial intelligence, The Turing
test is an operational test; that is, it provides a concrete way to determine whether the entity
is intelligent. The test involves a human interrogator who is in one room, another human
being in second room, and an artificial entity in a third room. The interrogator is allowed to
communicate with both the other human and the artificial entity only with a textual device
such as a terminal. The interrogator is asked to distinguish the other human from the artificial
entity based on answers to questions posed by the interrogator. If the interrogator cannot do
this, the Turing test is passed and we say that the artificial entity is intelligent. The computer
is interrogated by a human via a teletype. It passes if the human cannot decide what is at the
other end a computer or human.
Human? Human?
Machine? Machine?
Room A Room B
Room C
Human Interrogator
Fig. 1.1. Pictorial Representation of Turing Test
1.2.2. Chinese room Experiment
Searle [1980] took exception to the Turing test with his Chinese room thought
experiment. The experiment proceeds as follows: Suppose that we have successfully
developed a computer program that appears to understand Chinese. That is, the program
takes sentences written with Chinese characters as input, processes the characters, and outputs
sentences written using Chinese characters. If it is able to convince a Chinese interrogator
that it is a human, then the Turing test would be passed. Searle asks “does the program
literally understand Chinese or is it only simulating the ability to understand Chinese?” To
address this question, Searle proposes that he could sit in a closed room holding a book
containing English translation of the program, and adequate paper and pencils to carry out
the instructions of the program by hand. The Chinese interrogator could then provide Chinese
sentences through a slot in the door, Searle could process them using the program’s
instructions, and send Chinese sentences back through the same slot. Searle says that he has
performed the exact same task as the computer that passed the Turing test. That is, each is
following a program that simulates intelligent behavior. However, Searle notes that he does
not speak Chinese. Therefore, since he does not understand Chinese, the reasonable
conclusion is that the computer does not understand Chinese either. Searle argues that if the
computer does not understand the conversation, then it is not thinking, and therefore it does
not have an intelligent mind. Searle formulated the philosophical position known as strong
AI, which is as follows: The accurately programmed computer has mind, meaning that
, INTRODUCTION TO ARTIFICIAL INTELLIGENCE 1.3
computers can understand programs if they are correctly written in a language. Based on his
Chinese room experiment, Searle concludes that strong AI is not possible. Searle’s paper
resulted in a great deal of controversy and discussion for some time to come. The position
that computers could appear and behave intelligently, but not necessarily understand, is
called weak AI. The essence of the matter is whether a computer could actually have a mind
(strong AI) or could only simulate a mind (weak AI).
1.3. THE HISTORY OF ARTIFICIAL INTELLIGENCE
1. The Thinking of Artificial Intelligence (1943-1955)
There are number of examples available in past which can be related to that kind of
work which belongs to AI category, but Alan Turing is known as first person who first think
a complete vision of AI in his 1950 article “Computing Machinery and Intelligence.” In
it, he define the Turing test, machine learning, genetic algorithms, and reinforcement learning.
2. The Birth of Artificial Intelligence (1956)
In 1956 McCarthy meet to Minsk, Claude Shannon, and Nathaniel Rochester and make
a team together for research purpose. Claude Shannon and Nathaniel Rochester are U.S.
researchers expert in automata theory, neural network, and artificial intelligence. They all
together organized a two-month workshop at Dartmouth in the summer of 1956. The most
important achievement of this workshop is the agreement to adopt McCarthy’s suggested
new name to this field called artificial intelligence.
3. Early Journey of Artificial Intelligence (1952-1969)
Many researchers devote their time to increase the field of artificial intelligence.
4. General Problem Solver (GPS)
GPS was a computer program Developed in 1957 by Herbert Simon and Allen Newell for
development of universal problem solver machine. This program was a first program that thinks
somehow like human think. Herbert Gelernter developed a Geometry Theorem Solver, which
can be used to solve theorem quickly. Lisp was invented by John McCarthy in 1958 while he was
at the Massachusetts Institute of Technology. In 1963, McCarthy started the AI lab at Stanford.
5. Generation of Knowledge Based Systems (1966-1973)
During this span of time there are two most important knowledge based system was
introduced they are Dendral, and computer software expert system. Today an expert system
is a popular system for doing expert tasks.
6. AI Becomes an Industry (1980-present)
There are many project started in this age for example Japan started a project to built a
computer that can run on Prolog.
7. The Return of Neural Networks (1986-present)
Neural network is introduced in this period which become a powerfully tool in learning
today. This is used to increase the efficiency of system like fingerprint recognition system.
8. Hidden Markov Model and Bayesian Network (1987-present)
Hidden Markov model and Bayesian network introduced in this age. Today hidden
Markov models (HMMs) is become a tool for prediction. We are using various applications
