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SLIDE 1
MGIT-HARINATH
Introduction to
Artificial Intelligence
K. Harinath,
Assistant Professor,
Department of IT,
MGIT.
SLIDE 2
Can Machines Think??
MGIT-HARINATH
SLIDE 3
INTELLIGENCE
MGIT-HARINATH
SLIDE 4
What is Intelligence??
MGIT-HARINATH
SLIDE 5
Involved in Intelligence
MGIT-HARINATH
SLIDE 6
Intelligent Systems
MGIT-HARINATH
SLIDE 7
What is AI??
MGIT-HARINATH
SLIDE 8
Definitions of AI
MGIT-HARINATH
SLIDE 9
AI Systems
MGIT-HARINATH
SLIDE 10
HI vs AI (Pros)
MGIT-HARINATH
SLIDE 11
HI vs AI (Cons)
MGIT-HARINATH
SLIDE 12
MGIT-HARINATH
“Like
People”
“Rationally”
Think
Cognitive
Science
Laws of
Thought
Act Turing Test
Rational
Agents
Boundaries of AI ?
SLIDE 13
MGIT-HARINATH
What is AI ?
Systems that think like humans Systems that think rationality
``The exciting new effort to make
computers think ... machines with minds,
in the full and literal sense'' (Haugeland,
1985)
``The automation of activities that we
associate with human thinking, activities
such as decision-making, problem
solving, learning ...'' (Bellman, 1978)
``The study of mental faculties through the
use of computational models'' (Charniak
and McDermott, 1985)
``The study of the computations that make
it possible to perceive, reason, and act''
(Winston, 1992)
Systems that act like humans Systems that act like rationality
``The art of creating machines that
perform functions that require intelligence
when performed by people'' (Kurzweil,
1990)
``The study of how to make computers do
things at which, at the moment, people
are better'' (Rich and Knight, 1991)
``A field of study that seeks to explain and
emulate intelligent behavior in terms of
computational processes'' (Schalkoff,
1990)
``The branch of computer science that is
concerned with the automation of
intelligent behavior'' (Luger and
Stubblefield, 1993)
SLIDE 14
MGIT-HARINATH
Acting humanly: The Turing Test approach
? The Turing Test, proposed by Alan Turing (Turing, 1950), was
designed to provide a satisfactory operational definition of
intelligence.
? The computer would need to possess the following
capabilities:
1. Natural language processing to enable it to communicate successfully in
English (or some other human language);
2. Knowledge representation to store information provided before or during the
interrogation;
3. Automated reasoning to use the stored information to answer questions and
to draw new conclusions;
4. Machine learning to adapt to new circumstances and to detect and
extrapolate patterns.
? To pass the total Turing Test, the computer will need
? Computer Vision
? Robotics
SLIDE 15
MGIT-HARINATH
Thinking humanly: The cognitive modeling approach
- Program thinks like a human ..!
We need to get inside the actual workings of human minds.
There are three ways:
– through introspection--trying to catch our own thoughts as they
go by
– or through psychological experiments.
– Brain Imaging
Cognitive science brings together
? Computer Models of AI and
? Experimental Techniques from Psychology
SLIDE 16
CS vs AI
MGIT-HARINATH
SLIDE 17
MGIT-HARINATH
Thinking rationality: The Logical approach
? Ensure that all actions performed by computer are
justifiable (“rational”)
? Rational = Conclusions are provable from inputs and
prior knowledge
? Problems:
– Representation of informal knowledge is difficulty
– Hard to define “provable” plausible reasoning
– Combinatorial explosion: Not enough time or space to prove
desired conclusions.
Facts and Rules
in Formal Logic
Theorem Prover
SLIDE 18
MGIT-HARINATH
Acting rationally: The rational agent approach
? Rational behavior : doing the right thing ( that which is
expected to maximize goal achievement, given the available
information).
? Rational Agent is one that acts to achieve the best outcomes
or, when there is uncertainty, the best expected outcome.
Rational agents do the best they can
given their resources
SLIDE 19
MGIT-HARINATH
Rational Agents
? Adjust amount of reasoning according to
available resources and importance of
the result
? This is one thing that makes AI hard
very few resources lots of resources
no thought
“reflexes”
Careful, deliberate
reasoning
limited,
approximate
reasoning
SLIDE 20
AI (Advantages and Disadvantages)
MGIT-HARINATH
SLIDE 21
Eliza
MGIT-HARINATH
SLIDE 22
Deep Blue
MGIT-HARINATH
SLIDE 23
Self-Driving Cars
MGIT-HARINATH
SLIDE 24
IBM-Watson
MGIT-HARINATH
SLIDE 25
Robotics
MGIT-HARINATH
SLIDE 26
Robocop
MGIT-HARINATH
SLIDE 27
NLP
MGIT-HARINATH
SLIDE 28
Vision
MGIT-HARINATH
SLIDE 29
Captcha
MGIT-HARINATH
SLIDE 30
Wolfram Alpha
MGIT-HARINATH
SLIDE 31
StarCraft
MGIT-HARINATH
SLIDE 32
Counting Calories
MGIT-HARINATH
SLIDE 33
AI-Other Disciplines
MGIT-HARINATH
SLIDE 34
History of AI
MGIT-HARINATH
SLIDE 35
Cond.
MGIT-HARINATH
SLIDE 36
Cond.
MGIT-HARINATH
SLIDE 37
MGIT-HARINATH
Areas of Study in AI
? Reasoning, optimization, resource allocation
– planning, scheduling, real-time problem solving,
intelligent assistants, internet agents
? Natural Language Processing
– information retrieval, summarization, understanding,
generation, translation
? Vision
– image analysis, recognition, scene understanding
? Robotics
– grasping/manipulation, locomotion, motion planning,
mapping
SLIDE 38
MGIT-HARINATH
Where are we now?
? SKICAT: a system for automatically classifying the
terabytes of data from space telescopes and identifying
interesting objects in the sky. 94% classification
accuracy, exceeds human abilities.
? Deep Blue: the first computer program to defeat
champion Garry Kasparov.
? Pegasus: a speech understanding program that is a
travel agent (1-877-LCS-TALK).
? Jupiter: a weather information system (1-888-573-
TALK)
? HipNav: a robot hip-replacement surgeon.
SLIDE 39
MGIT-HARINATH
Where are we now?
? Navlab: a Ford escort that steered itself from
Washington DC to San Diego 98% of the way on its own!
? Google news: autonomous AI system that assembles
“live” newspaper
? DS1: a NASA spacecraft that did an autonomous flyby
an asteroid.
? Credit card fraud detection and loan approval
? Search engines
? Proverb: solves NYT puzzles as well as the best
humans.
SLIDE 40
MGIT-HARINATH
Surprises in AI research
? Tasks difficult for humans have turned out to be
“easy”
– Chess
– Checkers, Othello, Backgammon
– Logistics planning
– Airline scheduling
– Fraud detection
– Sorting mail
– Proving theorems
– Crossword puzzles
SLIDE 41
MGIT-HARINATH
Surprises in AI research
? Tasks easy for humans have turned out to be
hard.
– Speech recognition
– Face recognition
– Composing music/art
– Autonomous navigation
– Motor activities (walking)
– Language understanding
– Common sense reasoning (example: how many legs
does a fish have?)
SLIDE 42
Applications of Artificial Intelligence
? Robotic vehicles
? Speech recognition
? Logistics planning
? Robotics
? Spam filtering
? Game playing
? Machine Translation
? Medicine
? Tele Communications
? Banking
MGIT-HARINATH

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Artificial Intelligence-Introduction

  • 1. SLIDE 1 MGIT-HARINATH Introduction to Artificial Intelligence K. Harinath, Assistant Professor, Department of IT, MGIT.
  • 2. SLIDE 2 Can Machines Think?? MGIT-HARINATH
  • 4. SLIDE 4 What is Intelligence?? MGIT-HARINATH
  • 5. SLIDE 5 Involved in Intelligence MGIT-HARINATH
  • 7. SLIDE 7 What is AI?? MGIT-HARINATH
  • 8. SLIDE 8 Definitions of AI MGIT-HARINATH
  • 10. SLIDE 10 HI vs AI (Pros) MGIT-HARINATH
  • 11. SLIDE 11 HI vs AI (Cons) MGIT-HARINATH
  • 13. SLIDE 13 MGIT-HARINATH What is AI ? Systems that think like humans Systems that think rationality ``The exciting new effort to make computers think ... machines with minds, in the full and literal sense'' (Haugeland, 1985) ``The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning ...'' (Bellman, 1978) ``The study of mental faculties through the use of computational models'' (Charniak and McDermott, 1985) ``The study of the computations that make it possible to perceive, reason, and act'' (Winston, 1992) Systems that act like humans Systems that act like rationality ``The art of creating machines that perform functions that require intelligence when performed by people'' (Kurzweil, 1990) ``The study of how to make computers do things at which, at the moment, people are better'' (Rich and Knight, 1991) ``A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes'' (Schalkoff, 1990) ``The branch of computer science that is concerned with the automation of intelligent behavior'' (Luger and Stubblefield, 1993)
  • 14. SLIDE 14 MGIT-HARINATH Acting humanly: The Turing Test approach ? The Turing Test, proposed by Alan Turing (Turing, 1950), was designed to provide a satisfactory operational definition of intelligence. ? The computer would need to possess the following capabilities: 1. Natural language processing to enable it to communicate successfully in English (or some other human language); 2. Knowledge representation to store information provided before or during the interrogation; 3. Automated reasoning to use the stored information to answer questions and to draw new conclusions; 4. Machine learning to adapt to new circumstances and to detect and extrapolate patterns. ? To pass the total Turing Test, the computer will need ? Computer Vision ? Robotics
  • 15. SLIDE 15 MGIT-HARINATH Thinking humanly: The cognitive modeling approach - Program thinks like a human ..! We need to get inside the actual workings of human minds. There are three ways: – through introspection--trying to catch our own thoughts as they go by – or through psychological experiments. – Brain Imaging Cognitive science brings together ? Computer Models of AI and ? Experimental Techniques from Psychology
  • 16. SLIDE 16 CS vs AI MGIT-HARINATH
  • 17. SLIDE 17 MGIT-HARINATH Thinking rationality: The Logical approach ? Ensure that all actions performed by computer are justifiable (“rational”) ? Rational = Conclusions are provable from inputs and prior knowledge ? Problems: – Representation of informal knowledge is difficulty – Hard to define “provable” plausible reasoning – Combinatorial explosion: Not enough time or space to prove desired conclusions. Facts and Rules in Formal Logic Theorem Prover
  • 18. SLIDE 18 MGIT-HARINATH Acting rationally: The rational agent approach ? Rational behavior : doing the right thing ( that which is expected to maximize goal achievement, given the available information). ? Rational Agent is one that acts to achieve the best outcomes or, when there is uncertainty, the best expected outcome. Rational agents do the best they can given their resources
  • 19. SLIDE 19 MGIT-HARINATH Rational Agents ? Adjust amount of reasoning according to available resources and importance of the result ? This is one thing that makes AI hard very few resources lots of resources no thought “reflexes” Careful, deliberate reasoning limited, approximate reasoning
  • 20. SLIDE 20 AI (Advantages and Disadvantages) MGIT-HARINATH
  • 34. SLIDE 34 History of AI MGIT-HARINATH
  • 37. SLIDE 37 MGIT-HARINATH Areas of Study in AI ? Reasoning, optimization, resource allocation – planning, scheduling, real-time problem solving, intelligent assistants, internet agents ? Natural Language Processing – information retrieval, summarization, understanding, generation, translation ? Vision – image analysis, recognition, scene understanding ? Robotics – grasping/manipulation, locomotion, motion planning, mapping
  • 38. SLIDE 38 MGIT-HARINATH Where are we now? ? SKICAT: a system for automatically classifying the terabytes of data from space telescopes and identifying interesting objects in the sky. 94% classification accuracy, exceeds human abilities. ? Deep Blue: the first computer program to defeat champion Garry Kasparov. ? Pegasus: a speech understanding program that is a travel agent (1-877-LCS-TALK). ? Jupiter: a weather information system (1-888-573- TALK) ? HipNav: a robot hip-replacement surgeon.
  • 39. SLIDE 39 MGIT-HARINATH Where are we now? ? Navlab: a Ford escort that steered itself from Washington DC to San Diego 98% of the way on its own! ? Google news: autonomous AI system that assembles “live” newspaper ? DS1: a NASA spacecraft that did an autonomous flyby an asteroid. ? Credit card fraud detection and loan approval ? Search engines ? Proverb: solves NYT puzzles as well as the best humans.
  • 40. SLIDE 40 MGIT-HARINATH Surprises in AI research ? Tasks difficult for humans have turned out to be “easy” – Chess – Checkers, Othello, Backgammon – Logistics planning – Airline scheduling – Fraud detection – Sorting mail – Proving theorems – Crossword puzzles
  • 41. SLIDE 41 MGIT-HARINATH Surprises in AI research ? Tasks easy for humans have turned out to be hard. – Speech recognition – Face recognition – Composing music/art – Autonomous navigation – Motor activities (walking) – Language understanding – Common sense reasoning (example: how many legs does a fish have?)
  • 42. SLIDE 42 Applications of Artificial Intelligence ? Robotic vehicles ? Speech recognition ? Logistics planning ? Robotics ? Spam filtering ? Game playing ? Machine Translation ? Medicine ? Tele Communications ? Banking MGIT-HARINATH
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