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Artificial Intelligence (CSE)
UNIT-I
1.1 Introduction
Formal Definition of AI:
AI is a branch of computer science which is concerned with the study and creation of computer
systems that exhibit
some form of intelligence
OR
those characteristics which we associate with intelligence in human behavior
AI is a broad area consisting of different fields, from machine vision, expert systems to the
creation of machines that can "think". In order to classify machines as "thinking", it is necessary
to define intelligence.
Intelligence:
Intelligence is a property of mind that encompasses many related mental abilities, such as the
capabilities to
⚫ reason
⚫ plan
⚫ solve problems
⚫ think abstractly
⚫ comprehend ideas and language and
⚫ learn
Intelligent Systems:
An intelligent system is a system that can imitate, automate some intelligent behaviors of human
being. Expert systems, intelligent agents and knowledge-based systems are examples
of intelligent systems. Intelligent systems perform search and optimization along with learning
capabilities. So they are technologically advanced machines that perceive and respond to the
world around them. The field of intelligent systems also focuses on how these systems interact
with human users in changing and dynamic physical and social environments.
Categories of AI System
⚫ Systems that think like humans
⚫ Systems that act like humans
⚫ Systems that think rationally
⚫ Systems that act rationally
Systems that think like humans
Most of the time it is a black box where we are not clear about our thought process. One has
to know functioning of brain and its mechanism for possessing information. It is an area of
cognitive science. The stimuli are converted into mental representation. Cognitive processes
,MEDSTUDY.COM
manipulate representation to build new representations that are used to generate actions. Neural
network is a computing model for processing information similar to brain.
Systems that act like humans
The overall behavior of the system should be human like. It could be achieved by observation
Systems that think rationally
Such systems rely on logic rather than human to measure correctness. For thinking rationally
or logically, logic formulas and theories are used for synthesizing outcomes.
For example,
given John is a human and all humans are mortal then one can conclude logically that John
is mortal
Not all intelligent behavior are mediated by logical deliberation.
Systems that act rationally
Rational behavior means doing right thing. Even if method is illogical, the observed behavior
must be rational.
Foundations of AI
Foundation of AI is based on
Philosophy
Mathematics
Economics
Neuroscience
Control Theory
Linguistics
Computer Engineering
Psychology
Philosophy:
⚫ Can formal rules be used to draw valid conclusions?
⚫ How does the mind arise from a physical brain?
⚫ Where does knowledge come from?
⚫ How does knowledge lead to action?
Mathematics:
o More formal logical methods
⚫ Boolean logic
⚫ Fuzzy logic
o Uncertainty
⚫ The basis for most modern approaches to handle uncertainty in AI
applications can be handled by Probability theory, modal and temporal logics
,MEDSTUDY.COM
Economics:
⚫ How should we make decisions so as to maximize payoff?
⚫ How should we do this when others may not go along?
⚫ How should we do this when the payoff may be far in the future?
Neuroscience:
⚫ How do the brain works?
o Early studies (1824) relied on injured and abnormal people to understand what
parts of brain work
o More recent studies use accurate sensors to correlate brain activity to human
thought
By monitoring individual neurons, monkeys can now control a computer
mouse using thought alone
o How close are we to have a mechanical brain?
Parallel computation, remapping, interconnections,….
Control Theory:
o Machines can modify their behavior in response to the environment (sense/action loop)
Water-flow regulator, steam engine governor, thermostat
o The theory of stable feedback systems (1894)
Build systems that transition from initial
state to goal state with minimum energy
In 1950, control theory could only describe
linear systems and AI largely rose as a
response to this shortcoming
Linguistics:
⚫ How does language relate to thought?
⚫ Speech demonstrates so much of human intelligence
o Analysis of human language reveals thought taking place in ways not understood
in other settings
Children can create sentences they have never heard before
⚫ Language and thought are believed to be tightly intertwined
Computer Engineering:
⚫ How can we build an efficient computer ?
Psychology:
⚫ How do humans and animals think and act ?
, MEDSTUDY.COM
History of AI
Maturation / Gestation of Artificial Intelligence (1943-1952):
⚫ Year 1943: The first work which is now recognized as AI was done by Warren
McCulloch and Walter pits in 1943. They proposed a model of artificial neurons.
⚫ Year 1949: Donald Hebb demonstrated an updating rule for modifying the connection
strength between neurons. His rule is now called Hebbian learning.
⚫ Year 1950: The Alan Turing who was an English mathematician and pioneered Machine
learning in 1950. Alan Turing publishes "Computing Machinery and Intelligence" in
which he proposed a test. The test can check the machine's ability to exhibit intelligent
behavior equivalent to human intelligence, called a Turing test.
The birth of Artificial Intelligence (1952-1956):
⚫ Year 1955: An Allen Newell and Herbert A. Simon created the "first artificial
intelligence program which was named as "Logic Theorist". This program had proved 38
of 52 Mathematics theorems, and find new and more elegant proofs for some theorems.
⚫ Year 1956: The word "Artificial Intelligence" first adopted by American Computer
scientist John McCarthy at the Dartmouth Conference. For the first time, AI coined as an
academic field.
⚫ At that time high-level computer languages such as FORTRAN, LISP, or COBOL were
invented. And the enthusiasm for AI was very high at that time.
The Golden years-Early enthusiasm (1956-1974):
⚫ Year 1966: The researchers emphasized developing algorithms which can solve
mathematical problems. Joseph Weizenbaum created the first chatbot in 1966, which was
named as ELIZA.
Artificial Intelligence (CSE)
UNIT-I
1.1 Introduction
Formal Definition of AI:
AI is a branch of computer science which is concerned with the study and creation of computer
systems that exhibit
some form of intelligence
OR
those characteristics which we associate with intelligence in human behavior
AI is a broad area consisting of different fields, from machine vision, expert systems to the
creation of machines that can "think". In order to classify machines as "thinking", it is necessary
to define intelligence.
Intelligence:
Intelligence is a property of mind that encompasses many related mental abilities, such as the
capabilities to
⚫ reason
⚫ plan
⚫ solve problems
⚫ think abstractly
⚫ comprehend ideas and language and
⚫ learn
Intelligent Systems:
An intelligent system is a system that can imitate, automate some intelligent behaviors of human
being. Expert systems, intelligent agents and knowledge-based systems are examples
of intelligent systems. Intelligent systems perform search and optimization along with learning
capabilities. So they are technologically advanced machines that perceive and respond to the
world around them. The field of intelligent systems also focuses on how these systems interact
with human users in changing and dynamic physical and social environments.
Categories of AI System
⚫ Systems that think like humans
⚫ Systems that act like humans
⚫ Systems that think rationally
⚫ Systems that act rationally
Systems that think like humans
Most of the time it is a black box where we are not clear about our thought process. One has
to know functioning of brain and its mechanism for possessing information. It is an area of
cognitive science. The stimuli are converted into mental representation. Cognitive processes
,MEDSTUDY.COM
manipulate representation to build new representations that are used to generate actions. Neural
network is a computing model for processing information similar to brain.
Systems that act like humans
The overall behavior of the system should be human like. It could be achieved by observation
Systems that think rationally
Such systems rely on logic rather than human to measure correctness. For thinking rationally
or logically, logic formulas and theories are used for synthesizing outcomes.
For example,
given John is a human and all humans are mortal then one can conclude logically that John
is mortal
Not all intelligent behavior are mediated by logical deliberation.
Systems that act rationally
Rational behavior means doing right thing. Even if method is illogical, the observed behavior
must be rational.
Foundations of AI
Foundation of AI is based on
Philosophy
Mathematics
Economics
Neuroscience
Control Theory
Linguistics
Computer Engineering
Psychology
Philosophy:
⚫ Can formal rules be used to draw valid conclusions?
⚫ How does the mind arise from a physical brain?
⚫ Where does knowledge come from?
⚫ How does knowledge lead to action?
Mathematics:
o More formal logical methods
⚫ Boolean logic
⚫ Fuzzy logic
o Uncertainty
⚫ The basis for most modern approaches to handle uncertainty in AI
applications can be handled by Probability theory, modal and temporal logics
,MEDSTUDY.COM
Economics:
⚫ How should we make decisions so as to maximize payoff?
⚫ How should we do this when others may not go along?
⚫ How should we do this when the payoff may be far in the future?
Neuroscience:
⚫ How do the brain works?
o Early studies (1824) relied on injured and abnormal people to understand what
parts of brain work
o More recent studies use accurate sensors to correlate brain activity to human
thought
By monitoring individual neurons, monkeys can now control a computer
mouse using thought alone
o How close are we to have a mechanical brain?
Parallel computation, remapping, interconnections,….
Control Theory:
o Machines can modify their behavior in response to the environment (sense/action loop)
Water-flow regulator, steam engine governor, thermostat
o The theory of stable feedback systems (1894)
Build systems that transition from initial
state to goal state with minimum energy
In 1950, control theory could only describe
linear systems and AI largely rose as a
response to this shortcoming
Linguistics:
⚫ How does language relate to thought?
⚫ Speech demonstrates so much of human intelligence
o Analysis of human language reveals thought taking place in ways not understood
in other settings
Children can create sentences they have never heard before
⚫ Language and thought are believed to be tightly intertwined
Computer Engineering:
⚫ How can we build an efficient computer ?
Psychology:
⚫ How do humans and animals think and act ?
, MEDSTUDY.COM
History of AI
Maturation / Gestation of Artificial Intelligence (1943-1952):
⚫ Year 1943: The first work which is now recognized as AI was done by Warren
McCulloch and Walter pits in 1943. They proposed a model of artificial neurons.
⚫ Year 1949: Donald Hebb demonstrated an updating rule for modifying the connection
strength between neurons. His rule is now called Hebbian learning.
⚫ Year 1950: The Alan Turing who was an English mathematician and pioneered Machine
learning in 1950. Alan Turing publishes "Computing Machinery and Intelligence" in
which he proposed a test. The test can check the machine's ability to exhibit intelligent
behavior equivalent to human intelligence, called a Turing test.
The birth of Artificial Intelligence (1952-1956):
⚫ Year 1955: An Allen Newell and Herbert A. Simon created the "first artificial
intelligence program which was named as "Logic Theorist". This program had proved 38
of 52 Mathematics theorems, and find new and more elegant proofs for some theorems.
⚫ Year 1956: The word "Artificial Intelligence" first adopted by American Computer
scientist John McCarthy at the Dartmouth Conference. For the first time, AI coined as an
academic field.
⚫ At that time high-level computer languages such as FORTRAN, LISP, or COBOL were
invented. And the enthusiasm for AI was very high at that time.
The Golden years-Early enthusiasm (1956-1974):
⚫ Year 1966: The researchers emphasized developing algorithms which can solve
mathematical problems. Joseph Weizenbaum created the first chatbot in 1966, which was
named as ELIZA.
