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CS 531/331: Introduction to AI

CS 531/331: Introduction to AI. Mian Muhammad Awais Room 416 awais@lums.edu.pk. Course Description. Course home page : suraj/lums.edu.pk/~cs331a05 Contacts :lecture notes, tutorials, assignment, grading, office hours, etc. Textbooks:

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CS 531/331: Introduction to AI

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  1. CS 531/331: Introduction to AI Mian Muhammad Awais Room 416 awais@lums.edu.pk CS 331: Dr M M Awais (LUMS)

  2. Course Description Course home page: suraj/lums.edu.pk/~cs331a05 Contacts:lecture notes, tutorials, assignment, grading, office hours, etc. Textbooks: 1) Luger: Artificial Intelligence: Structures and Strategies for Complex Problem-solving Fourth Edition (Available as Reading package) 2) S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, First or Second Edition (HANDOUTS) Grading: Quizzes (15%) Lab/Assignments/Project (15%), Midterm test (30%) Final exam (40%) At least 2 Lab Assignments where attendance will be compulsory and will be taken. Midterm test (in class) and final exam (as per schedule) CS 331: Dr M M Awais (LUMS)

  3. TA Support/Office Hours • Natasha Qureshi (TA) natasha@lums.edu.pk Office hours (see the website) • Instructor Office Hours: 3 to 4 PM Every day except Friday CS 331: Dr M M Awais (LUMS)

  4. Course Outline • Introduction and Problem Solving (Today’s Lecture) • Part I: Knowledge Representation • Part II: Informed Search Methods • Part III: Planning / Reasoning/Expert Systems • Part IV: Learning CS 331: Dr M M Awais (LUMS)

  5. Book Chapters • Book Chapters and articles will be announced as we go along • Slides will be available at the website and the common’s folder CS 331: Dr M M Awais (LUMS)

  6. Informal Feedback Mechanism • Every Two Weeks an anonymous questionnaire will be circulated to evaluate the course • Your comments will be welcomed to improve the course • We will also have course progress discussion after every two weeks CS 331: Dr M M Awais (LUMS)

  7. Questions CS 331: Dr M M Awais (LUMS)

  8. AI Dimensions 1) Modeling: Thought process/reasoning vs. behavior/action • 2) Evaluation: Success according to human standards vs. success according to an ideal concept of intelligence: rationality. CS 331: Dr M M Awais (LUMS)

  9. What is AI? Views of AI fall into four categories: Our Focus is "ACTING RATIONALLY" CS 331: Dr M M Awais (LUMS)

  10. Acting humanly: Meaning "Can machines behave like Humans?" CS 331: Dr M M Awais (LUMS)

  11. Acting humanly: Turing Test • Turing (1950) "Computing machinery and intelligence": • 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 CS 331: Dr M M Awais (LUMS)

  12. CS 331: Dr M M Awais (LUMS)

  13. Objections :- Turning Test Most AI Programs Are Not Flexible In Nature May Not Be Able to Answer Emotional Questions CS 331: Dr M M Awais (LUMS)

  14. Thinking humanly “Can machines think like humans” • Requires scientific theories of internal activities of the brain • Cognitive Modeling CS 331: Dr M M Awais (LUMS)

  15. Thinking humanly: cognitive modeling • 1960s "cognitive revolution": information-processing psychology • Validation Requires • Predicting and testing behavior of human subjects (top-down) • Direct identification from neurological data (bottom-up) • Cognitive Science and Cognitive Neuroscience • Distinct from AI CS 331: Dr M M Awais (LUMS)

  16. Thinking humanly: Some References • Daniel C. Dennet. Consciousness explained. • M. Posner (edt.) Foundations of cognitive science • Francisco J. Varela et al. The Embodied Mind • J.-P. Dupuy. The mechanization of the mind CS 331: Dr M M Awais (LUMS)

  17. Thinking rationally “Laws of Thought” “Can machines think rationally” 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 CS 331: Dr M M Awais (LUMS)

  18. Thinking rationally • Aristotle: what are correct arguments/thought processes? • Mathematics and Philosophy to Modern AI • Problems: • Not all intelligent behavior is mediated by logical deliberation • What is the purpose of thinking? What thoughts should I have? A reference; • Ivan Bratko, Prolog programming for artificial intelligence. CS 331: Dr M M Awais (LUMS)

  19. Acting rationally “Can machines behave rationally” • 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 CS 331: Dr M M Awais (LUMS)

  20. Rational Agents • An agent is an entity that perceives and acts • Every thing to be discussed should be taken in the context of : RATIONAL AGENTS • Abstractly, an agent is a function from percept histories to actions: [f: P*A] • For a given class of environments/tasks, Rational Agents sought best performance CS 331: Dr M M Awais (LUMS)

  21. Limitations:Rational Agents • Computational limitations make perfect rationality unachievable • (this leads to) Design best program for given machine resources References Michael Wooldridge. Reasoning about rational agents. CS 331: Dr M M Awais (LUMS)

  22. Definition: AI Systems Artificial Systems that behave rationally CS 331: Dr M M Awais (LUMS)

  23. Another Definition: AI? More inclined towards acting and thinking humanly Computer based solution of complex problems through the application of processes that are analogous to the Human Intelligence CONTROVERSIAL ISSUE (How to define Intelligence) CS 331: Dr M M Awais (LUMS)

  24. Intelligence - Establishes Relationships - Perception and Comprehension - Generalization Ability - Memory/Differentiation Chair vs Table Spoon vs Fork Reasoning + Learning Intelligent Beings Intelligent Systems CS 331: Dr M M Awais (LUMS)

  25. AI Though GroupsStrong BelieversWeak Believers CS 331: Dr M M Awais (LUMS)

  26. Weak AI?Computation Consciousness Brain has ingredients that are • Non - computational • Simulating consciousness is not possible Computational + Non Computational BRAIN CS 331: Dr M M Awais (LUMS)

  27. Strong AI ? Consciousness - “is some complicated computation” “Computers can achieve or even exceed all Human Capacities once high computational speeds are achieved” Brains Are Computers of MEAT? CS 331: Dr M M Awais (LUMS)

  28. Scope of AI Based Techniques Main focus Problems that do not have algorithmic solutions, or are very complex Vague, uncertain and poor-defined systems Systems with decision - making problems (Examples?) CS 331: Dr M M Awais (LUMS)

  29. Knowledge Diagnostic Experts Coding Experts Example Tasks Game Playing • Rules are well defined • algorithmic solutions are very complex • Formalization is easy Automated Reasoning • Theorem proving • Formal logic/ knowledge representation. Expert Systems Mimic experts such as doctors CS 331: Dr M M Awais (LUMS)

  30. Human Machine Natural Language Processing • Computer learn human languages • Machine Translation • Speech Synthesis Planning And Robotics • Artificial Pets. • Efforts to make “machines” - Responsive - Flexible e.g., Path Planning CS 331: Dr M M Awais (LUMS)

  31. Summary: AI? • Innovative Extension of Philosophy: • Understand and BUILD intelligent entities • Formal Origin after WWII • Highly interdisciplinary • Variety of subfields • This course will discuss some of them CS 331: Dr M M Awais (LUMS)

  32. 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 CS 331: Dr M M Awais (LUMS)

  33. 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 CS 331: Dr M M Awais (LUMS)

  34. State of the art AI • 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 CS 331: Dr M M Awais (LUMS)

  35. First Reading Assignment(Write a Two Page Summary on the Scope of AI)Submission: Email the article to Instructor /TA by Friday 5:00 pm • Luger’s Chapter One: Introduction Other References: Alexander Igor’s Impossible minds (Help Material Available in the Library) CS 331: Dr M M Awais (LUMS)

  36. Topics Covered Today • Luger (Some of the discussion is from Stuart and Norvig) • Part I • Chapter 1 • Articles 1.1 to 1.4 • Practice: • Attempt Exercise Questions • Especially: Qs 1 to 7, 10 to 12 CS 331: Dr M M Awais (LUMS)

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