1. CS 531/331: Introduction to AI
Mian Muhammad Awais
Room 416
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)
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: Thinking humanly
Thinking rationally
Acting humanly
Acting rationally
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. May Not Be Able to Answer Emotional Questions
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. “Can machines think like humans”
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. “Can machines think rationally”
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 A reference;
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. “Can machines behave rationally”
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?
Computer based solution of complex problems through the application of processes that are analogous to the
Human Intelligence
More inclined towards acting and thinking humanly
CONTROVERSIAL ISSUE
(How to define Intelligence)
CS 331: Dr M M Awais (LUMS)

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

25. AI Though Groups Strong Believers Weak Believers
CS 331: Dr M M Awais (LUMS)

26. Computational + Non Computational
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. Brains Are Computers of MEAT?
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. Example Tasks Game Playing Automated Reasoning Expert Systems
Rules are well defined
algorithmic solutions are very complex
Formalization is easy
Automated Reasoning
Theorem proving
Formal logic/ knowledge representation.
Coding
Knowledge
Diagnostic
Experts
Expert Systems
Mimic experts such as doctors
CS 331: Dr M M Awais (LUMS)

30. Natural Language Processing
Computer learn human languages
Machine Translation
Speech Synthesis
Human Machine
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
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
AI becomes an industry
Neural networks return to popularity
AI becomes a science
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: 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)