CS 462: Introduction to Artificial Intelligence

1. CS 462: Introduction to Artificial Intelligence This course advocates the physical-symbol system hypothesis formulated by Newell and Simon in 1976. It states that intelligence is a functional property and is completely independent of any physical embodiment. Alternative less-symbolic paradigms are neural networks and evolutionary computation (of which genetic algorithms are the most prominent example).

2. What is Intelligence? Property attributed to people: She is intelligent = She knows a lot. = She thinks fast. = She talks much. = She learns quickly. Intelligence = Knowledge + ability to perceive, feel, comprehend, process, communicate, judge, learn.

3. What is Artificial Intelligence? • An interdisciplinary field aiming at developing techniques and tools for solving problems that people at good at. • Existing definitions of the field advocate everything from replicating human intelligence to simply solving knowledge-intensive tasks. Some examples: “Artificial Intelligence is a study of complex information processing problems that often have their roots in some aspect of biological information processing. The goal of the subject is to identify solvable and interesting information processing problems, and solve them.” -- David Marr. “Artificial Intelligence is the design, study and construction of computer programs that behave intelligently.” -- Tom Dean. “Artificial Intelligence is the enterprise of constructing a physical symbol system that can reliably pass the Turing test.” -- Matt Ginsberg.

4. Goals of Artificial Intelligence • Scientific goal: understand the mechanisms behind human intelligence. • Engineering goal: develop concepts and tools for building intelligent agents capable of solving real world problems. • Intelligent Simulation: creating realistic simulated worlds for affordable training and simulation. • Intelligent Information Resources: supporting the use of national / world-wide information infrastructure. • Intelligent Project Coaches: help in design and operation of complex systems. • Robot Teams: performing dangerous operations and tasks.

5. Examples of intelligent agents: • Knowledge-based systems: capture knowledge that people have which are relevant to a problem. • Common sense reasoning systems: capture knowledge that people commonly hold which is why this knowledge is not explicitly communicated. • Learning systems: posses the ability to expend their knowledge based on the accumulated experience. • Natural language understanding systems: support dialog in English/French/Japanese/… • Game playing systems. • Intelligent robots. • Speech and vision recognition systems.

6. Introduction to LISP • Why LISP? • Especially designed for symbol manipulation. • Provides built-in support for lists. • Automatic storage management (no need to keep track of memory allocation). • Interactive environment, which allows programs to be developed step by step. That is, if a change is to be introduced, only changed functions need to be recompiled. • Recommended books: 1. These lecture notes are based on Winston and Horn LISP, 3rd edition, AddisonWesley, 1993 2. For advanced topics and additional examples refer to Norvig P. Artificial Intelligence Programming, Morgan Kaufman, 1992.

7. Basic terminology • Atoms: word-like indivisible objects which can be numbers or symbols. • Lists: sentence-like objects formed from atoms or other lists, and enclosed in parentheses. • S-expressions: compositions of atoms and lists. • Procedures: step by step specifications how to do something. • Primitives: procedures supplied by the LISP itself Example: (+ 5 6) • User-defined procedures: procedures introduced by the programmer. Example: (students 'anna) • Program: a collection of procedures working together.

8. S-expressions • An s-expression can have other s-expressions nested in it. Examples: (+ (* 5 7) ( / 2 4)) (This (is a dog) (or a cat)) • Expressions can be interpreted both, procedurally and declaratively. • If interpreted procedurally, an expression provides a direction for doing something. Such an expression is called a form, and its first element is the name of a procedure to be used to produce the value. • The process of computing the value of an expression is called evaluation. • If interpreted declaratively, expressions represent data. Data and procedures have the same syntax.

9. Evaluation of atoms • The value of a number is the number itself. Example: 5 ==> 5 • The value of a string is the string itself. Example: “Nice day” ==> “Nice day” • The value of the symbol T is T (true). • The value of the symbol NIL is NIL (false). • The symbol NIL and the empty list ( ) are the same thing. • Variables are names of memory locations. The contents stored in a given memory cell is the value of the variable serving as a name of this location. Example: Let x be a variable, and 5 be the contents of the memory cell called x. Then, the value of x is 5.

10. Numbers • Integers: 179, 45 • Ratio: 5/7, 7/9 • Floating point: 5.2, 7.9 • Examples: * (/ 25 5) 5 * (/ 46 9) 46/9 ; do not divide evenly * (float (/ 46 9)) 5.111111 * (round (/ 46 9)) 5 ; the nearest integer 1/9 ; the remainder

11. * (- 6) -6 * (- -6) 6 * (max 5 7 2) 7 * (min 5 7 2) 2 * (sqrt (* (+ 1 3) (* 2 2))) 4.0 * (+ (round (/ 22 7)) (round (/ 7 3))) 5 * (+ 2 2.5) 4.5 * (expt 3 6) 729 * (sqrt 81) 9.0 * (sqrt 82) 9.055386 * (abs 6) 6 * (abs -6) 6 More numeric primitives

12. Consider the list (A (B (C))). It can be represented by means of the following diagram: Representation of atoms and lists in a computer memory A B These boxes are called cons cells. C

13. 1 leading byte, called the data type byte. It holds information indicating that the particular group of 9 bytes is part of a list (i.e. a cons cell). 2 groups of 4 bytes each, representing pointers. Each pointer is an address -- the first one to the memory location containing the first element of the list, and the second one to the memory location storing the rest of the list. The second pointer of the last element of each list contains zeros (representing NIL and empty list). i.e. no cons cell corresponds to the empty list. Each cons cell consists of 9 bytes:

14. Example: Given the list (Education is power), build a new list from it and the atom University. *(cons 'University '(Education is power)) (UNIVERSITY EDUCATION IS POWER) To implement this, LISP maintains a list of free boxes (cons cells), called the free-storage list. CONS removes the first box from the free-storage list, and deposits new pointers into it. The CONS primitive builds new lists

15. Education is power Free storage list ... University

16. Consider the list (A B . C). Here (B . C) is called adotted pair, and is represented as follows: To construct the list (A B C), we write: * (cons 'A (cons 'B (cons 'C NIL))) To construct the list (A B . C), we write: * (cons 'A (cons 'B 'C)) Dotted pairs B C