1

Lecture # 1Introduction to Artificial Intelligence

ByNADEEM MAHMOOD

ASSISTANT PROFESSORDEPARTMENT OF COMPUTER SCIENCE, UNIVERSITY OF

KARACHI

2

MCS-616COURSE INFORMATION Course Supervisor: Nadeem Mahmood Teaching Assistant: Qaiser Iqbal Textbook: S. Russell and P. Norvig Artificial Intelligence: A

Modern Approach Prentice Hall, 2003, Second Edition Grading: Class participation & Assignments (20%),

Project(20%), Quiz(10%), Final(50%) Class participation is very important which includes participation

in both lectures and tutorials (attendance, asking and answering questions, presenting solutions to tutorial questions).

Note that attendance at every lecture and tutorial will be taken and constitutes part of the class participation grade.

3

Outline

Course overview What is AI? A brief history The state of the art

4

Course overview

Introduction and Agents (chapters 1,2) Search (chapters 3,4,5,6) Logic (chapters 7,8,9) Planning (chapters 11,12) Uncertainty (chapters 13,14) Learning (chapters 18,20) Natural Language Processing (chapter 22,23)

5

What is “Artificial Intelligence?”

Problems that are easy forhumans but hard for computers?• A set of techniques?(Logic, probability, utility, etc.)• Is it science or engineering?• Machines that think like humans?• Machines that act like humans?• Machines that act rationally?

6

What is AI?

Views of AI fall into four categories:

Thinking humanly Thinking rationally

Acting humanly Acting rationally

The textbook advocates "acting rationally"

7

Acting humanly: Turing Test

Turing (1950) "Computing machinery and intelligence": "Can machines think?" "Can machines behave intelligently?" Operational test for intelligent behavior: the Imitation Game

Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes

Anticipated all major arguments against AI in following 50 years Suggested major components of AI: knowledge, reasoning,

language understanding, learning

8

Thinking humanly: cognitive modeling 1960s "cognitive revolution": information-processing

psychology Requires scientific theories of internal activities of the

brain -- How to validate? Requires

1) Predicting and testing behavior of human subjects (top-down)

or 2) Direct identification from neurological data (bottom-up)

Both approaches (roughly, Cognitive Science and Cognitive Neuroscience)

are now distinct from AI

9

Thinking rationally: "laws of thought" Aristotle: what are correct arguments/thought

processes? Several Greek schools developed various forms of

logic: notation and rules of derivation for thoughts; may or may not have proceeded to the idea of mechanization

Direct line through mathematics and philosophy to modern AI

Problems: 1. Not all intelligent behavior is mediated by logical

deliberation2. What is the purpose of thinking? What thoughts

should I have?

10

Acting rationally: rational agent

Rational behavior: doing the right thing The right thing: that which is expected to

maximize goal achievement, given the available information

Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action

11

Rational agents

An agent is an entity that perceives and acts This course is about designing rational agents Abstractly, an agent is a function from percept

histories to actions:[f: P* A]

For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance

Caveat: computational limitations make perfect rationality unachievable design best program for given machine resources

12

What Can AI Do?

Quiz: Which of the following can be done at present? Play a decent game of table tennis? Drive safely along a curving mountain road? Drive safely along Telegraph Avenue? Buy a week's worth of groceries on the web? Buy a week's worth of groceries at Berkeley Bowl? Discover and prove a new mathematical theorem? Converse successfully with another person for an hour? Perform a complex surgical operation? Unload a dishwasher and put everything away? Translate spoken English into spoken Swedish in real time? Write an intentionally funny story?

13

Natural Language

Speech technologies Automatic speech recognition (ASR) Text-to-speech synthesis (TTS) Dialog systemsLanguage processing technologies Machine translation:Aux dires de son président, la commission serait en mesure de le faire .According to the president, the commission would be able to do so .Il faut du sang dans les veines et du cran .We must blood in the veines and the courage .There is no backbone , and no teeth . Information extraction Information retrieval, question answering Text classification, spam filtering, etc…

14

Vision (Perception)

15

Robotics

Robotics Part mech. eng. Part AI Reality muchharder thansimulations! Technologies Vehicles Rescue Soccer! Lots of automation…

16

Game Playing

May, '97: Deep Blue vs. Kasparov First match won against world-champion ``Intelligent creative'' play 200 million board positions per second! Humans understood 99.9 of Deep Blue's moves Can do the same now with a big PC cluster Open question: How does human cognition deal with the search space

explosion of chess? Or: how can humans compete with computers at all?? 1996: Kasparov Beats Deep Blue “I could feel - I could smell - a new kind of intelligence across

the table.” 1997: Deep Blue Beats Kasparov “Deep Blue hasn't proven anything.”

17

Logic

Logical systems Theorem provers NASA fault diagnosis Question answering Methods: Deduction systems Constraint satisfaction Satisfiability solvers (huge advances here!)

18

Decision Making

Many applications of AI: decision making Scheduling, e.g. airline routing, military Route planning, e.g. mapquest Medical diagnosis, e.g. Pathfinder system Automated help desks Fraud detection

… the list goes on.

19

AI prehistory Philosophy Logic, methods of reasoning, mind as

physical system foundations of learning, language,

rationality Mathematics Formal representation and proof algorithms,

computation, (un)decidability, (in)tractability,probability

Economics utility, decision theory Neuroscience physical substrate for mental activity Psychology phenomena of perception and motor control,

experimental techniques Computer building fast computers

engineering Control theory design systems that maximize an objective

function over time Linguistics knowledge representation, grammar

20

Abridged history of AI 1943 McCulloch & Pitts: Boolean circuit model of brain 1950 Turing's "Computing Machinery and Intelligence" 1956 Dartmouth meeting: "Artificial Intelligence" adopted 1952—69 Look, Ma, no hands! 1950s Early AI programs, including Samuel's checkers

program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine

1965 Robinson's complete algorithm for logical reasoning 1966—73 AI discovers computational complexity

Neural network research almost disappears 1969—79 Early development of knowledge-based systems 1980-- AI becomes an industry 1986-- Neural networks return to popularity 1987-- AI becomes a science 1995-- The emergence of intelligent agents

21

State of the art Deep Blue defeated the reigning world chess champion Garry

Kasparov in 1997 Proved a mathematical conjecture (Robbins conjecture)

unsolved for decades No hands across America (driving autonomously 98% of the

time from Pittsburgh to San Diego) During the 1991 Gulf War, US forces deployed an AI logistics

planning and scheduling program that involved up to 50,000 vehicles, cargo, and people

NASA's on-board autonomous planning program controlled the scheduling of operations for a spacecraft

Proverb solves crossword puzzles better than most humans