1. CS 531: AI CS 331: Introduction to AI
Dr Mian Muhammad Awais
Room 416
Robotics and Intelligent Computing (RICE), Group
CS 531: Dr M M Awais (LUMS)

2. Course Description Course home page: TBA
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%)
Practice (15%),
Midterm test (30%)
Final exam (40%)
Practice Options:
At least 2 Lab Assignments where attendance will be compulsory and will be taken.
Critical reviews of interesting papers
Take Home/In class Assignments (LISP/PROLOG)
CS 531: Dr M M Awais (LUMS)

3. TA Support/Office Hours
TA 1: Umar Faiz
Office hours (TBA, see the website)
TA 2: TBA
Instructor Office Hours (room 416):
3 to 4 PM Every day except Friday
CS 531: Dr M M Awais (LUMS)

4. Course Outline (Core Areas) Very Basic
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 531: Dr M M Awais (LUMS)

5. Course Outline (Specialized Areas)
To be decide as the course progresses
Some options are:
NLP
Speech Processing
(On going project at LUMS, 1.0 million, 3 years)
Agent Technology
(Submitted project, 5.9 million, 3 years)
Imitative Learning
(On going project at LUMS, 4.3 million, 3 years)
Case Based Reasoning
etc
CS 531: Dr M M Awais (LUMS)

6. Course Format Each Class 100 minutes not 75 minutes Core Areas:
Basic stuff,
same as CS 331,
will go through it quickly,
tested with take home assignments,
Midterm and finals will have at least 60% from the core areas.
Special Areas:
High level brief discussion,
tested with assignments, quizzes,
maximum of 40% covered in exams
CS 531: Dr M M Awais (LUMS)

7. Book Chapters
Book Chapters and articles will be announced as we go along
Slides will be available at the website and in the common’s folder
Details to be announced later
CS 531: Dr M M Awais (LUMS)

8. Informal Feedback Mechanism LETS IMPROVE AS WE MARCH
Roughly Every Two Weeks an anonymous questionnaire will be circulated to evaluate the course
Your comments will be welcomed to improve the course as we go along
(DONOT WAIT TILL THE END)
Course progress discussion
CS 531: Dr M M Awais (LUMS)

9. Questions
CS 531: Dr M M Awais (LUMS)

10. One is to use the power of computers to augment human thinking,
TWO PURPOSES of AI.
One is to use the power of computers to augment human thinking,
just as we use motors to augment human or horse power. Robotics and expert systems are major branches of that.
The other is to use a computer's artificial intelligence to understand how humans think.
In a humanoid way. If you test your programs not merely by what they can accomplish, but how they accomplish it, they you're really doing cognitive science; you're using AI to understand the human mind.
Herbert Simon
CS 531: Dr M M Awais (LUMS)

11. Thought process/reasoning vs. behavior/action
AI Dimensions
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 531: Dr M M Awais (LUMS)

12. What is AI? Views of AI fall into four categories: Thinking humanly
Thinking rationally
Acting humanly
Acting rationally
CS 531: Dr M M Awais (LUMS)

13. “Can machines think like humans”
Thinking humanly
“Can machines think like humans”
Requires scientific theories of internal activities of the brain, psychological experiments are required
Studied in Cognitive Modeling
CS 531: Dr M M Awais (LUMS)

14. 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 531: Dr M M Awais (LUMS)

15. 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 531: Dr M M Awais (LUMS)

16. “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 531: Dr M M Awais (LUMS)

17. 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 531: Dr M M Awais (LUMS)

18. “Can machines behave like Humans?”
Acting humanly
“Can machines behave like Humans?”
“Why and How” is not important
Do what ever you can
CS 531: Dr M M Awais (LUMS)

19. 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 531: Dr M M Awais (LUMS)

20. CS 531: Dr M M Awais (LUMS)

21. 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 531: Dr M M Awais (LUMS)

22. Chinese Room
   
The Turing Test was the first attempt at resolving the question of machine intelligence.
It was a behavioral test, judging intelligence based not on inner processes, or faithfulness to neuronal structure, but purely on a computer's ability to verbally communicate.
This approach elicited numerous objections:
Why should behaviour be the final test on intelligence
How can behavior suffice if the internal mechanisms controlling it are nothing like a human being's?
How can a conversation capture all of human intelligence?
These questions essentially reduced themselves to the question of whether one could pass the Turing Test, that is, produce passable conversational speech, while still possessing no 'real' intelligence. This argument has been stated in numerous ways, but perhaps none more eloquent than
John Searle's Chinese Room metaphor.
CS 531: Dr M M Awais (LUMS)

23. Searle Counter Example
Imagine a room, with a man trapped inside. The man speaks no Chinese. Someone slips a piece of paper under the door with Chinese writing on it.
Having puzzled over it for a moment, he notices that there is a book in the room titled "What to do if someone slides some Chinese writing under the door."
The book, he finds, is actually an enormous set of instructions for producing new Chinese symbols based on what comes in. The rules instruct him on how to produce new Chinese symbols, based on the ones received. They are all if-then type statements describing a pattern in the text and the appropriate action or response.
He follows these rules, using the piece of paper handed to him, and produces a new sheet, which he slides back under the door.
The next day, another sheet comes in, he passes the completed sheet back out.
Outside, the world is amazed that this room can actually understand Chinese, that the room is intelligent. Inside though, we know that the man understands no Chinese whatsoever!
CS 531: Dr M M Awais (LUMS)

24. Conclusion
What Searle describes is a system that produces intelligent, meaningful output, in the absence of true understanding. If you accept this counter-example, then the Turing Test is doomed. The Chinese Room would pass the Turing test, even though it lacks understanding and intelligence. Searle's argument has, naturally, produced its own share of furious debate, and several strong counter-arguments have been levelled at it.
CS 531: Dr M M Awais (LUMS)

25. References
(best resource)
CS 531: Dr M M Awais (LUMS)

26. “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 531: Dr M M Awais (LUMS)

27. What is AI? Views of AI fall into four categories: Thinking humanly
Thinking rationally
Acting humanly
Acting rationally
Our Focus is "ACTING RATIONALLY"
CS 531: Dr M M Awais (LUMS)

28. 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 531: Dr M M Awais (LUMS)

29. Limitations:Rational Agents
Computational limitations make perfect rationality unachievable
Design best program for given machine resources
References
Michael Wooldridge. Reasoning about rational agents.
CS 531: Dr M M Awais (LUMS)

30. Definition: AI Systems
Artificial Systems that behave rationally Or
limited rationality
CS 531: Dr M M Awais (LUMS)

31. Other Aspects
Read it yourself
CS 531: Dr M M Awais (LUMS)

32. 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 531: Dr M M Awais (LUMS)

33. 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 531: Dr M M Awais (LUMS)

34. Manifestation of intelligence is
through Behavior
CS 531: Dr M M Awais (LUMS)

35. AI Though Groups Strong Believers Weak Believers
CS 531: Dr M M Awais (LUMS)

36. Computational + Non Computational
Weak AI? Computation Consciousness
Brain has ingredients that are
Non - computational
Simulating consciousness is not possible
Computational + Non Computational
BRAIN
CS 531: Dr M M Awais (LUMS)

37. 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 531: Dr M M Awais (LUMS)

38. Strong and Weak AI
CS 531: Dr M M Awais (LUMS)

39. 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 531: Dr M M Awais (LUMS)

40. 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 531: Dr M M Awais (LUMS)

41. 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 531: Dr M M Awais (LUMS)

42. 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 531: Dr M M Awais (LUMS)

43. 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 531: Dr M M Awais (LUMS)

44. 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 531: Dr M M Awais (LUMS)

45. 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 531: Dr M M Awais (LUMS)

46. First Reading Assignment (Write a Two Page Summary on What you think AI is) Submission: the article to Instructor /TA by Friday 5:00 pm (or in folder submission_1 in Cs 531AI)
Luger’s
Chapter One: Introduction
Other References:
Alexander Igor’s Impossible minds
(Help Material Available in the Library)
CS 531: Dr M M Awais (LUMS)

47. 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 531: Dr M M Awais (LUMS)