PDF Dr. Amr Abdullah Munshi LECTURE 1. INTRODUCTION - uqu.edu.sa

(1)

LECTURE 1. INTRODUCTION

INSTRUCTOR: DR. AMR ABDULLAH MUNSHI ARTIFICIAL INTELLIGENCE

INSTRUCTOR

Dr. Amr Abdullah Munshi

•

Office: 1^stfloor, room 1083

•

Email: [email protected]

•

Office hours: by appointment or fixed date

DR. AMR MUNSHI, 2019

2

BASICS

•

Lectures: Tuesdays 14:00-14:50 and Wednesdays 08:00-09:40

•

Laboratories:

Wednesdays 16:00-17:40 and Thursdays 16:00-16:50 (Group 1) Mondays 08:00-09:40 and Wednesdays 13:00-13:50 (Group 2)

PREREQUISITES

•14012402-4 Algorithms

•Solid programming background

TEXTBOOK

•Artificial Intelligent: A Modern Approach,3^rdEdition, Russell and Norvig, 2009, Prentice Hall, ISBN: 0136042597

(2)

ATTENDANCE POLICY

Students are expected to attend every class, to arrive on time, and to participate in all class activities. Missing class more than 25% with or without a legitimate excuse will result in withdrawal from the course. If you must miss class for any reason you are responsible for any work that you miss, and missing class is no excuse for not turning in an assignment.

5

LATE SUBMISSION POLICY

All submissions must be turned in on the due date. Late submissions turned in within 24 hours from the due date will receive a 50% penalty. Submissions will not be accepted more than 24 hours late.

6

RECORDING OF LECTURES

Recording is permitted only with the prior written consent of the instructor. If a lecture is to be recorded, the instructor must notify the class that this is taking place and the person making the recording may need to obtain the permission of all other individuals that appear in the recording.

ACADEMIC INTEGRITY

Umm Al-Qura University is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are urged to familiarize themselves with the provisions of the Student Responsibilites (online at

https://uqu.edu.sa/studaff/App/FILES/11155), and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence.

(3)

NOTES

•

No calculators or any other electronic devices are allowed at the exam.

•

NO MAKEUP EXAMS.

•

Instructor reserves the right to change the course outline and the deadlines based on students' progress and coverage of the material.

9

COURSE EVALUATION

•

Attendance (5%)

•

Assignments ~4-5 (15%)

•

Lab + Lab Assignments (10%)

•

Project + Presentation in groups of 3 to 5 (15%)

•

Midterm (15%)

•

Final Exam (40%)

10

TOPICS AND APPROX. TIMELINE

•Chapter 1: Introduction. What is AI (1 week)

•Chapter 2: Intelligent Agents (~2 weeks)

•Chapter 3 & 4: Search (~3 weeks)

•Chapter 5: Game Search (~1 week)

•Chapter 6: Constrain Satisfaction Problems (~2 weeks)

•Chapter 7: Logical Agents (~1 week)

•Chapter 18: Learning from Examples (1.5 week)

WHAT IS INTELLIGENCE ?

•

Are these intelligent?

(4)

WHAT IS INTELLIGENCE ?

•

What about these?

13

•

What about this?

14

•

Abstract concepts, mathematics, language, problem solving, memory, logical reasoning, planning ahead, emotions, morality, ability to learn/adapt, etc…

INTRODUCTION TO AI

What is AI ?

(5)

INTRODUCTION TO AI

17

INTRODUCTION TO AI

18

INTRODUCTION TO AI

•

“A branch of Computer Science. Examines how we can achieve intelligent behaviour through computation.”

•

“The reproduction of human reasoning and intelligent behavior by computational methods.”

INTRODUCTION TO AI

(6)

INTRODUCTION TO AI

21

INTRODUCTION TO AI

•Subareas of AI:

Computer vision Speech recognition Machine learning Neural networks Robotics …..

22

INTRODUCTION TO AI

•

Together these formalisms and algorithms form the foundation of our attempt to understand intelligence as a computational process.

•

In this course we will study some of these formalism and algorithm techniques, and see how they can be used to achieve various degrees of intelligence.

ACTING HUMANLY: THE TURING TEST APPROACH

•

Turing Test:

A computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer.

•

Weak Turing type tests:

(7)

ACTING HUMANLY

1. Natural language processingto enable it to communicate successfully in English 2. Knowledge representation to store what it knows or hears

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

5. Computer vision to perceive objects 6. Roboticsto manipulate objects and move about

25

THINKING HUMANLY

•

We must have some way of determining how humans think!

Psychological experiments Brain imaging

•

Once we have a sufficiently precise theory of the mind, it becomes possible to express the theory as a computer program.

26

THINKING RATIONALLY

•

Logic

“Socrates is a man; all men are mortal; therefore, Socrates is mortal.”

ACTING RATIONALLY

•

An agentis just something that acts

•

A rational agent is one that acts so as to achieve the best outcome or, when there is uncertainty, the best expected outcome.

•

Achieving perfect rationality—always doing the right thing—is not feasible in complicated environments.

(8)

HUMAN INTELLIGENCE

•

In general there are various reasons why trying to mimic humans might not be the best approach to AI:

- Computers and Humans have different architecture with quite different abilities

- Numerical computations - Visual and sensory processing

- Massively and slow parallel vs. fast serial

29

HUMAN INTELLIGENCE

•

We know very little about how the human brain performs its higher level processes.

•

Neuroscience has been very influential in some areas of AI. For example, in robotic sensing, vision processing, etc.

•

Humans might not be best comparison?

- Don’t always make the best decisions

- Computer intelligence can aid in our decision making

30

HUMAN INTELLIGENCE HISTORY OF AI

(9)

HISTORY OF AI

33

THE STATE-OF-THE-ART

•Robotic vehicles

•Speech recognition

•Game playing

•Spam filtering

•Fraud detection

•Robotics

•Route planning

•Medical diagnosis

•Machine translation

•Product recommendations

34

THE STATE-OF-THE-ART

”These are just a few examples of artificial intelligence systems that exist today.

Not magic or science fiction—but rather science, engineering, and mathematics, to which this book provides an introduction.”

READINGS

•

1.1, 1.3 and 1.4

•