ARTIFICIAL INTELLIGENCE : Introduction , Introduction to Artificial Intelligence, Background and Applications, Turing Test and Rational Agent approaches to AI, Introduction to Intelligent Agents, their structure, behavior and environment. 2. Problem Solving and Searching Techniques Problem Characteristics, Production Systems, Control Strategies, Breadth First Search, Depth First Search, Hill climbing and its Variations, Heuristics Search Techniques: Best First Search, A* algorithm, Constraint Satisfaction Problem, Means-End Analysis, Introduction to Game Playing, Min-Max and Alpha-Beta pruning algorithms. 3. Knowledge Representation Introduction to First Order Predicate Logic, Resolution Principle, Unification, Semantic Nets, Conceptual Dependencies, Frames, and Scripts, Production Rules, Conceptual Graphs. Programming in Logic (PROLOG) 4. Dealing with Uncertainty and Inconsistencies Maintenance System, Default Reasoning, Probabilistic Reasoning, Bayesian Probabilistic Inference, Possible World Representations. 5. Understanding Natural Languages Parsing Techniques, Context-Free and Transformational Grammars, Recursive and Augmented Transition Nets.

1. Presentation
on
By
BHARAT BHUSHAN
Asst. Professor, Department of Computer Sc.
RLSY College, Ranchi
Buddha Science and Technical Institute, Ranchi
www.bharatsir.com
INTRODUCTION
ARTIFICIAL INTELLIGENCE

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Artificial Intelligence
UNIT-1 : INTRODUCTION
 Introduction to Artificial Intelligence
 Background and Applications
 Turing Test and Rational Agent
approaches to AI
 Introduction to Intelligent Agents
 Their structure
 Behavior and environment.

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Artificial Intelligence
The term artificial intelligence was first coined
by John McCarthy in 1956 when he held the
first academic conference on the subject.

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Artificial Intelligence
Introduction
Artificial Intelligence (AI) is a method of
making a computer, a computer-controlled
robot, or a software think intelligently like
the human mind.
AI is accomplished by studying
the patterns of the human brain and by
analyzing the cognitive process. The
outcome of these studies develops
intelligent software and systems.

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Artificial Intelligence
Background of AI
1956 : John McCarthy coined the term ‘artificial
intelligence’ and had the first AI conference.
1969 : Shakey was the first general-purpose
mobile robot built. It is now able to do things with
a purpose vs. just a list of instructions.
1997 : Supercomputer ‘Deep Blue’ was designed,
and it defeated the world champion chess player in
a match. It was a massive milestone by IBM to
create this large computer.

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Artificial Intelligence
Background of AI
2002 : The first commercially successful
robotic vacuum cleaner was created.
2005–2019 : Today, we have speech
recognition, robotic process automation
(RPA), a dancing robot, smart homes, and
other innovations make their debut.

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Artificial Intelligence
Background of AI
2020 : Baidu releases the LinearFold AI
algorithm to medical and scientific and
medical teams developing a vaccine
during the early stages of the
SARS-CoV-2 (COVID-19) pandemic.
The algorithm can predict the RNA
sequence of the virus in only 27 seconds,
which is 120 times faster than other
methods.

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Artificial Intelligence
Applications of AI

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Artificial Intelligence
Applications of AI
 E-Commerce
 Education
 Lifestyle
 Navigation
 Robotics
 Human Resource
 Healthcare
 Agriculture
 Gaming
 Automobiles
 Social Media
 Marketing
 Chatbots
 Finance

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Artificial Intelligence
Turing Test
In 1950, Alan Turing introduced a test to
check whether a machine can think like a
human or not, this test is known as the Turing
Test.
In this test, Turing proposed that the
computer can be said to be an intelligent if it
can mimic human response under specific
conditions.

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Artificial Intelligence
Rational Agent
A rational agent or rational being is a person
or entity that always aims to perform optimal
actions based on given premises and
information.
A rational agent can be anything that makes
decisions, typically a person, firm, machine,
or software.

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Artificial Intelligence
Example of Rational Agent
Consider the case of this Vacuum cleaner as a Rational
agent. It has the environment as the floor which it is
trying to clean. It has sensors like Camera's or dirt
sensors which try to sense the environment. It has the
brushes and the suction pumps as actuators which take
action.

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Artificial Intelligence
How Does a Rational Agent Work?
A rational agent is essentially a goal-based
agent. It assesses its environment by
considering what it is like. It then looks at
each available action in its arsenal and
determines how it will affect the
environment and help it attain its goal. It
tries out all the possible steps before
choosing the best one, the one that will
move it closest to its objective.

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Artificial Intelligence
How Does a Rational Agent Work?

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Artificial Intelligence
Simple Diagram to understand Rational Agent
A sensor could be a camera, an infrared device, a
sonar, an ultrasound, a radar, or a lidar in the image
above. It helps an AI robot determine an object’s or
its surroundings’ size, identify a thing, and
determine distances.
An effector, meanwhile, is any device that affects a
particular environment. It could be a robot’s legs,
wheels, arms, fingers, wings, or fins. Effectors are
also called “actuators.”

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Artificial Intelligence
Simple Diagram to understand Rational Agent
A sensor could be a camera, an infrared device, a
sonar, an ultrasound, a radar, or a lidar in the image
above. It helps an AI robot determine an object’s or
its surroundings’ size, identify a thing, and
determine distances.
An effector, meanwhile, is any device that affects a
particular environment. It could be a robot’s legs,
wheels, arms, fingers, wings, or fins. Effectors are
also called “actuators.”

17. Bharat Bhushan, Assistant Professor, RLSY College, Ranchi
Artificial Intelligence