1. CMPB454 ARTIFICIAL INTELLIGENCE (AI) CHAPTER 1.1 Background Information CHAPTER 1.1 Background Information Instructor: Alicia Tang Y. C.

2. AI : INTRODUCTORY LESSON u What Is Natural Intelligence? u What Is IQ? u What Is Artificial Intelligence? u What Machine Is Good At?

3. IQ of a person Mental Age IQ = -------------------------------- * 100 Chronological Age E.g. if a 20 years old person undergoes IQ test and the examiner determines his mental age as 18, hen his IQ is 90 ------------------> below average! Younger candidate case: 20/10 * 100 = 200 point

4. AI can be defined as the attempt to get real machines to behave like the ones in the movies.

5. AI : INTRODUCTORY LESSON u Heuristics Vs. Algorithmic. Logic u What Is Logic? u ______ + ________ = Traditional Program u _____ + _____________ = AI Program

6. AI : INTRODUCTORY LESSON u Father Of Artificial Intelligence – ALAN TURING u What is “Turing Test”? u Other Theorists : McDermott, McCarthy, Winston, Rich, Newell, Simon, Rosenblatt, etc.

7. Alan Turing(1912-1954)

8. SYMBOLIC PROCESSING It is a branch of Computer Science that deals with Symbolic, Non Algorithmic methods of problem solving. HEURISTICS It is the branch of Computer Science that deals with ways of representing knowledge using symbols rather than numbers and with rules- of-thumb for processing information.

9. HEURISTICS PROGRAMMING u HEURISTICS –developed through intuition, experience & judgment. –they do not represent (our) knowledge of design, rather, they represent guidelines through which a system may be operated. –often called ‘Rules of thumb’. u CHARACTERISTICS OF HEURISTICS t Screening FilteringPruning

10. HEURISTIC PROGRAMMING Should not be confused with computer programming. A program is a solution; programming is a procedure for obtaining a solution. Thus, heuristic programming is a procedure for finding the solution to a model consisting of ‘heuristics’.

11. u A human would normally take 20 years to acquire an IQ of approximately 120 point, but: –do we give computers a few years or so to gain knowledge (hence intelligence) to attain at the same level of competency? u How does a baby learn? S/he sees, hears, reads, etc. for countless number of times. u Anticipated for  Medical officers to be involved in AI research.… … brain study... Neurophysiology Some Background Study

12. LANGUAGES FOR AI PROBLEM SOLVING u Two Levels of Abstraction: t Symbol level t Knowledge level u Symbol Level: –Concerns with the particular formalisms used to represent knowledge such as logic or production rules. –Concerns with the structures used to organize knowledge.

13. u Knowledge Level: t what queries will be made? t how new knowledge could be added? t what objects and relations are necessary? t can the system reasons despite of incompleteness of information?

14. REQUIREMENTS FOR AI LANGUAGE  Support of Symbolic Computation –implementation of a set of operation on symbolic rather than numeric data. –predicate calculus is a powerful tool for constructing qualitative descriptions of a domain.  Support of Symbolic Computation –implementation of a set of operation on symbolic rather than numeric data. –predicate calculus is a powerful tool for constructing qualitative descriptions of a domain.

15. u Flexibility of Control –AI cannot be achieved by the step-by- step execution of fixed sequence of instructions. –Production systems being the most important paradigm for building AI program. –Production rules can fire in virtually any order (not step-by-step) in response to a given situation.

16.  Support of Exploratory Programming Methodologies. –AI programs seldom respond to standard software approaches such as top-down design, stepwise refinement. –This is due to the nature of AI problems that they could be started & tested without having to completely produce the final specification. –In other words, most AI programs are initially poorly specified. –AI programming is inherently exploratory; the program is the vehicle through which we explore the problem area (domain) and discover solution strategies.  Support of Exploratory Programming Methodologies. –AI programs seldom respond to standard software approaches such as top-down design, stepwise refinement. –This is due to the nature of AI problems that they could be started & tested without having to completely produce the final specification. –In other words, most AI programs are initially poorly specified. –AI programming is inherently exploratory; the program is the vehicle through which we explore the problem area (domain) and discover solution strategies.

17. u Late Binding and Constraint Propagation –Often, the problems addressed by AI program (such as Prolog program) require that the values of certain entities to remain unknown until sufficient information is gathered to determine the assignment. –As constraints are accumulated, the set of possible values is reduced, ultimately converging on a solution.

18. u Clear and Well-defined Semantics. –This could be achieved by developing new languages that do not (to certain extent) conform to the architecture underlying von Neumann computer and be on the foundation of mathematical formalisms such as logic (Prolog). –Traditional programming languages are too complex in constructs and semantic definitions. They are not subject to self- proof. u Clear and Well-defined Semantics. –This could be achieved by developing new languages that do not (to certain extent) conform to the architecture underlying von Neumann computer and be on the foundation of mathematical formalisms such as logic (Prolog). –Traditional programming languages are too complex in constructs and semantic definitions. They are not subject to self- proof.

19. AI Systems Development Knowledge and expertise Can be tested (already) This is called __________

20. There is no MAGIC