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Topics in Artificial Intelligence

Topics in Artificial Intelligence. prof. dr hab. inż. Joanna Józefowska, http://www.cs.put.poznan.pl/jjozefowska. Curriculum. Introduction – overview of research topics in artificial intelligence Knowledge representation Space search as a general inference model

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Topics in Artificial Intelligence

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  1. Topics in Artificial Intelligence prof. dr hab. inż. Joanna Józefowska, http://www.cs.put.poznan.pl/jjozefowska

  2. Curriculum • Introduction – overview of research topics in artificial intelligence • Knowledge representation • Space search as a general inference model • Reasoning under uncertainty dr hab. inż. Joanna Józefowska, prof. PP

  3. References • Bolc L., Borodziewicz W., Wójcik M., Podstawy przetwarzania informacji niepewnej i niepełnej, PWN, Warszawa, 1991. • Bolc L., Zaremba J., Wprowadzenie do uczenia się maszyn, Akademicka Oficyna Wydawnicza RM, Warszawa, 1992. • Bolc L., J. Cytowski, Metody przeszukiwania heurystycznego, PWN, t1 1989, t2 1991. • Charniak E., Mc Dermot D., Introduction to Artificial Intelligence, Addison Wesley, 1985. • Churchland P.M., P. Smith-Churchland, Czy maszyna może myśleć?, Świat Nauki, lipiec 1991. • Greenfield S., Tajemnice mózgu, Świat Książki, Warszawa, 1998. • Guida G., C. Tasso, Design and Development of Knowledge-Based Systems, John Wiley 1994. • Harel D., Rzecz o istocie informatyki, wyd. 2, WNT Warszawa, 2000. • Lugger G., Stubblefield W.A., Artificial Intelligence and the Design of Expert Systems, The Benjamin/Cummings Publ. Comp. Inc., 1989. • Mulawka J., Systemy ekspertowe, Warszawa, WNT, 1996 • Neural Networks and Soft Computing, L. Rutkowski, R. Tadeusiewicz (eds.), Polish Neural Network Society, Częstochowa, 2000. • Niederliński A., Regułowe systemy ekspertowe, Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, Gliwice 2000. • Puppe F., Systematic Introduction to Expert Systems, Springer Verlag 1993. • Rich E., Artificial Intelligence, McGraw Hill, 1983. • Rich E., K. Knight, Artificial intelligence, McGraw Hill, New York, 1991. • Russell S. J., Norvig P., Artificial Intelligence. A modern approach, Prentice Hall, Inc. 1995. • Scarle J.R., Czy intelekt mózgu jest programem komputerowym?, Świat Nauki, lipiec 1991. • Sieci Neuronowe, W. Duch, J. Korbicz, L.Rutkowski, R. Tadeusiewicz, Biocybernetyka i Inżynieria Medyczna 2000, t. 6, Akademicka Oficyna Wydawnicza EXIT, Warszawa 2000. • Tadeusiewicz R., Elementarne wprowadzenie do techniki sieci neuronowych z przykładowymi programami, Akademicka Oficyna Wydawnicza PLJ, Warszawa 1998. dr hab. inż. Joanna Józefowska, prof. PP

  4. Artificial Intelligencemyths and reality dr hab. inż. Joanna Józefowska, prof. PP

  5. What is human intelligence? • Is it a single feature or a set of skills? • Can one learn it? • What is learning? • What is creativity? • What is intuition? • What is consciousness? • Can we build an intelligent machine? • How to check if a machine is intelligent? dr hab. inż. Joanna Józefowska, prof. PP

  6. Intelligence has been defined by prominent researchers in the field as : Binet and Simon (1905): the ability to judge well, to understand well, to reason well. Terman (1916): the capacity to form concepts and to grasp their significance. Wechsler (1939): the aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with the environment. Gardner (1986): the ability or skill to solve problems or to fashion products which are valued within one or more cultural settings. dr hab. inż. Joanna Józefowska, prof. PP

  7. Shall I compare thee to a summer’s day? Thou art. More lovely and more temperate: Rough winds do shake the darlings buds of May, And summer’s lease hath all too short a date; W. Shakespeare Linguistic intelligence • reading • writing • speaking • understanding • creativity dr hab. inż. Joanna Józefowska, prof. PP

  8. Personal intelligence Ma dwie odmiany: interpersonal – „people smart” intrapersonal –„self smart” dr hab. inż. Joanna Józefowska, prof. PP

  9. Logical-mathematical intelligence„number/reasoning smart” • abstract, symbolic thought • sequential reasoning skills • inductive and deductive thinking patterns E=mc2 dr hab. inż. Joanna Józefowska, prof. PP

  10. Kinesthetic intelligence – „Body smart” manipulate objects and use a variety of physical skills dr hab. inż. Joanna Józefowska, prof. PP

  11. Musical intelligence Musical intelligence is the capacity to discern pitch, rhythm, timbre, and tone.  • recognize • create • reproduce • reflect on music Słuchamy fragmentu IX symfonii Ludwiga van Beethovena dr hab. inż. Joanna Józefowska, prof. PP

  12. Spatial intelligence Spatial intelligence is the ability to think in three dimensions.  • mental imagery • spatial reasoning • image manipulation • graphic and artistic skills • an active imagination dr hab. inż. Joanna Józefowska, prof. PP

  13. The IQ Test and 7 types of intelligence by Gardner IQ = (Mental Age) / (Chronological Age) x 100 • linguistic intelligence • personal intelligence • interpersonal • intrapersonal • logical-mathematical intelligence • kinesthetic intelligence • musical intelligence • spatial intelligence Psychologist Howard Gardner Gardner, H. (1983). Frames of Mind: The theory of multiple intelligences. New York: Basic Books. Basic Books Paperback, 1985. Tenth Anniversary Edition with new introduction, New York: Basic Books, 1993. dr hab. inż. Joanna Józefowska, prof. PP

  14. General intelligence Charles Spearman G-factor Intelligence is not a collection of various aptitudes but the integration of various aptitudes into a coherent whole. Humans are smarter than computers because they can switch from Chess to Painting and see the connections between those fields, something that computers are completely unable to do. Intelligence is at least as much into the links between our various aptitudes that into the various aptitudes themselves and it is a serious mistake to reduce intelligence to the aptitudes that support it. dr hab. inż. Joanna Józefowska, prof. PP

  15. Intelligence and General intelligence • memory • creativity • imagination • common sense • intuition • emotions • morality dr hab. inż. Joanna Józefowska, prof. PP

  16. Famous meeting "Within ten years a digital computer will be the world's chess champion," Allen Newell said in 1957, "unless the rules bar it from competition." The Dartmouth Seminar 1956 Dartmouth College: John McCarthy Marvin Minsky Claude Shannon Nathaniel Rochester Princeton: Trenchard More IBM: Arthur Samuel MIT: Ray Solomonoff Oliver Selfridge Carnegie Tech: Allen Newell Herbert Simon dr hab. inż. Joanna Józefowska, prof. PP

  17. Artificial intelligence Thinking humanly Thinking rationally Acting humanly Acting rationally Source: Russel S.J., Norvig P., Artificial intelligence - a modern approach, Prentice Hall 1995. dr hab. inż. Joanna Józefowska, prof. PP

  18. The Turing test ? dr hab. inż. Joanna Józefowska, prof. PP

  19. Criticism of the Turing test • The Test provides a guarantee not of intelligence but of culturally-oriented human intelligence (see French, Robert M.: Subcognition and the Limits of the Turing Test). • The test is limited to solving symbolic tasks, it is not possible to verify perception or manual abilities, although they reflect human intelligence. dr hab. inż. Joanna Józefowska, prof. PP

  20. Defense of the Turing test • The only standard allowing to discover intelligence without defining its „true” nature. • It ignores the problem of internal computer inference mechanism and its consciousness. • The natural advantages of „living” object is reduced by the interface. dr hab. inż. Joanna Józefowska, prof. PP

  21. Mental faculties flavour, test, intuition dr hab. inż. Joanna Józefowska, prof. PP

  22. Application domains of artificial intelligence • Natural language processing • Image recognition • Automated reasoning • Games • Expert systems • Automatic learning • Action planning and robotics dr hab. inż. Joanna Józefowska, prof. PP

  23. Cognitivism or connectionism?Weak or strong artificial intelligence? dr hab. inż. Joanna Józefowska, prof. PP

  24. Conectionist model Cognitivist model • How do humans solve problems? • How does a human brain work? • Big number of identical simple units • Distributed and parallel processing • Failure resistance • Symbolic knowledge representation • Inference mechanism Complexity of learning Complexity of search dr hab. inż. Joanna Józefowska, prof. PP

  25. Physical symbol system hypothesis1976 - Allen Newell, Herbert A. Simon*) A physical symbol system consists of a set of entities, called symbols, which are physical patterns that can occur as components of another type of entity called an expression (or symbol structure). Hypothesis: A physical symbol system has the necessary and sufficient means for general intelligent action. *)Carnegie Tech - now Carnegie Mellon University dr hab. inż. Joanna Józefowska, prof. PP

  26. Knowledge representation The process and the result of formalization of knowledge in such a way, that it can be used automatically for problem solving. Search General technique for problem solving consisting in systematic exploration of all consecutive and alternative steps in the problem solving process. dr hab. inż. Joanna Józefowska, prof. PP

  27. Alfred N. Whitehead 1861-1947 Bernard Russel 1872-1970 Automated reasoning dr hab. inż. Joanna Józefowska, prof. PP

  28. Allen Newell 19.03.1927 - 19.07.1992 Herbert Simon 15.06.1916 - 9.02.2001 Logic Theorist - 1956 dr hab. inż. Joanna Józefowska, prof. PP

  29. First Order Logic (FOL) A = Z  F  P  S  {(, ), ,} A – set of symbols Z - variables x1, x2, ... F – function symbols: F1n, F2n, ... P – predicate symbols: P1n, P2n, ... S – logical symbols {, , , , , , } dr hab. inż. Joanna Józefowska, prof. PP

  30. Deduction Inference method based on modus ponens dr hab. inż. Joanna Józefowska, prof. PP

  31. Theory • (A1) man(X)  die(X) • (A2) man(sokrates) • 2. modus ponens Theorem: die(sokrates) Dowód: 1. X/sokrates in A1 (A1’) man(sokrates)  die(sokrates) man(sokrates) , man(sokrates)  die(sokrates) die(sokrates) dr hab. inż. Joanna Józefowska, prof. PP

  32. Operations in Logic Theorist Substitution: any variable may be substituted by an expresion. e.g. in (ØAÚ B) Û (A Þ B) we substitute ØA for B (ØA ÚØA) Û (AÞØA) (*) Replacement: an operator can be replaced by a definition. np. w wyrażeniu (ØA ÚØA) ÞØA zastępujemy operator Ú jego definicją (*) (A ÞØA) ÞØA Modus ponens (reguła odrywania): [(AÞ B)Ù A] B dr hab. inż. Joanna Józefowska, prof. PP

  33. Logic Theorist - summary • Newella, Simona and Shawa 1956 • Proved theorems from the first chapter of Principia Mathematica • Knowledge representation: FOL • Inference: deduction • Comparison of expressions: unification • Problems: complexity dr hab. inż. Joanna Józefowska, prof. PP

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