1 Lecture # 1 Introduction to Artificial Intelligence By NADEEM MAHMOOD ASSISTANT PROFESSOR DEPARTMENT OF COMPUTER SCIENCE, UNIVERSITY OF KARACHI

2 MCS-616 COURSE 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 for humans 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 humanlyThinking rationally Acting humanlyActing 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 deliberation 2. 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 systems Language 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 Part mech. eng. Part AI Reality much harder than simulations! 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 PhilosophyLogic, methods of reasoning, mind as physical system foundations of learning, language, rationality MathematicsFormal representation and proof algorithms, computation, (un)decidability, (in)tractability, probability Economicsutility, decision theory Neurosciencephysical substrate for mental activity Psychology phenomena of perception and motor control, experimental techniques Computer building fast computers engineering Control theorydesign systems that maximize an objective function over time Linguisticsknowledge representation, grammar

20 Abridged history of AI 1943 McCulloch & Pitts: Boolean circuit model of brain 1950 Turing's "Computing Machinery and Intelligence" 1956Dartmouth meeting: "Artificial Intelligence" adopted 1952—69Look, Ma, no hands! 1950sEarly AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine 1965Robinson's complete algorithm for logical reasoning 1966—73AI discovers computational complexity Neural network research almost disappears 1969—79Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science 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