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Artificial Intelligence (AI) Lecture No. 1

This lecture provides an overview of the core disciplines of Artificial Intelligence (AI), the contribution of other fields, the history of AI, and its various applications. It also explores the concepts of intelligence and the difference between intelligent computing and conventional computing.

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Artificial Intelligence (AI) Lecture No. 1

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  1. Artificial Intelligence(AI)Lecture No. 1

  2. Disciplines which form the core of AI- inner circle Fields which draw from these disciplines- outer circle. Robotics NLP (Natural Language Processing) Search, Reasoning, Learning Expert Systems Planning Computer Vision

  3. Agenda Intelligence Intelligence of computer Artificial intelligence Intelligent computing Vs Conventional computing Contribution of other fields to AI History of AI Applications of AI References

  4. Intelligence?

  5. Can Intelligence be defined? Intelligence can not be defined abstractly There are probably as many definitions of intelligence as there are experts who study it.

  6. Intelligence (defination) • from "Mainstream Science on Intelligence" (1994), an editorial statement by fifty-two researchers: • A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly (conceptually), comprehend complex ideas, learn quickly and learn from experience. • (Gottfredson, L.S., 1997).

  7. Intelligence • from "Intelligence: Knowns and Unknowns" (1995), a report published by the Board of Scientific Affairs of the American Psychological Association: • Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought. • (Neisser, 1997) and (Perloff, 1996)

  8. Other definitions of intelligence • capacity for learning, reasoning, understanding, and similar forms of mental activity; aptitude (ability) in grasping truths, relationships, facts, meanings, etc. • the faculty(perceptual powers of the mind ) of understanding. • knowledge of an event, circumstance, etc., received or imparted; news; information. • the gathering or distribution of information, especially secret information • www. dictionary.com

  9. Intelligence (summary) • Intelligence is the ability of: • abstract thought( Apart from a particular case or instance) • understanding • communication (The activity of conveying information) • Reasoning (Logical thinking) • Learning(Acquiring skill or knowledge) • planning (Process of thinking about what to do in the event of something happening) • problem solving

  10. Intelligence of computer • According to the British computer scientist Alan Turing's test in (1950): • “a computer would deserves to be called intelligent if it could deceive a human into believing that it was human.”

  11. Artificial Intelligence? ???

  12. Artificial Intelligence • “A branch of a computer science which studies the development of software and hardware which simulates human intelligence” • (Dr. Ghassan Issa)

  13. Artificial Intelligence • AI is the part of computer science concerned with designing intelligent computer systems, that is, computer systems that exhibit the characteristics we associate with intelligence in human behavior- • Understandinglanguages, • learning, • reasoning, • solving problems, and so on. • (Barr and Feigenbaum, 1981)

  14. Other Definitions of AI …. • “AI is the study of how to make computer do things at which, at the moment, people are better” • (Rich and Knight, 1991) • “AI is the study of idea that enable computers to be intelligent” • (Patrick H. Winston)

  15. “AI is a collection of hard problems which can be solved by humans and other living things, but for which we don’t have good algorithms for solving”. • e. g., understanding spoken natural language, medical diagnosis, circuit design, learning, self-adaptation, reasoning, chess playing, proving math theories, etc

  16. Intelligent computing Vs Conventional computing

  17. Intelligent computing Vs Conventional computing … • Conventional: • Based on algorithms whose instructions are stored in memory and executed in sequential way. • AI Computing: • Not based on algorithms but based on: • Knowledge base (symbolic representation) • Uses reasoning and inferencing over the knowledge base to search and perform pattern matching.

  18. Intelligent computing Vs Conventional computing …

  19. Contributions of other disciplines to AI Philosophy Logic, methods of reasoning, mind as physical system, foundations of learning, language,rationality (wisdom) Mathematics Formal representation and proof of algorithms, computation, (un)decidability, (in)tractability, probability Economics utility, decision theory Neuroscience how do brain process information (neuron operation) Psychology1- How do humans and animals think and act 2- phenomena of perception and motor control,experimental techniques Computer engineeringbuilding fast computers Control theory 1- How can artifacts (objects) operate under their own control? 2- design systems that maximize an objective function over time. Linguistics knowledge representation, grammar

  20. Abridged history of artificial intelligence • 1941 first electric computer was developed • 1943 McCulloch & Pitts: • Boolean circuit model of brain • 1949 first “stored program” computer was introduced • 1950 Turingproposed his “Turing Test” for intelligence. • 1955 early chess playing programs demonstrated • 1956in Dartmouth conference birth was given to: • "Artificial Intelligence" • 1957 LISP(List Processing) language by John McCarthy at MIT

  21. Abridged history of artificial intelligence 1965 expert system DENDRAL started at Stanford 1965 Robinson's complete algorithm for logical reasoning 1966 expert system MACSYMA started at MIT 1969—79 Early development of knowledge-based systems 1970 implementation of the Prolog language 1972 expert system MYCIN developed at Stanford 1972 SHRDLU natural language robot demonstrated at MIT

  22. Abridged history of artificial intelligence • 1980-- AI becomes an industry • 1981-- Commercial NLP system “Intellect” available from NLP group • 1986-- Neural networks return to popularity • 1987-- AI becomes a science • 1995-- The emergence of intelligent agents • 1995-2007 HLAI (Human Level AI): • AI should return to its roots of striving "machines that think, that learn” • Hays and Efros (2007) • discuss the problem of filling in holes in a photograph

  23. Abridged history of artificial intelligence • 2008--Artificial General Intelligence or AGI • AGI looks for a universal algorithm for learning and acting in any environment • (Halevy et al_ 2009) • learning algorithm

  24. Applications of AI Game playing General problem solving Expert system Natural language Processing Computer vision Robotics Education Others

  25. References Gottfredson, L.S. (1997). "Foreword to "intelligence and social policy""Intelligence24 (1): 1–12. doi:10.1016/S0160-2896(97)90010-6. http://www.udel.edu/educ/gottfredson/reprints/1997specialissue.pdf. Neisser, U.; Boodoo, G.; Bouchard Jr, T.J.; Boykin, A.W.; Brody, N.; Ceci, S.J.; Halpern, D.F.; Loehlin, J.C.; Perloff, R.; Sternberg, R.J.; Others, (1998). "Intelligence: Knowns and Unknowns". Annual Progress in Child Psychiatry and Child Development 1997. ISBN9780876308707. http://books.google.com/?id=gLWnmVbKdLwC&pg=PA95&dq=Intelligence:+Knowns+and+unknowns. Perloff, R.; Sternberg, R.J.; Urbina, S. (1996). "Intelligence: knowns and unknowns". American Psychologist51. Dr. Ghassan Issa, Artificial intelligence, retrieved from: http://www.uop.edu.jo/issa/ai/ai-part1.htm, retrieved date: 04 Oct, 2011.

  26. References • Crash Course in Artificial Intelligence and Expert systems by Louise E. Frenzel. • Chapter No.1 • Artificial Intelligence - A Modern Approach 3rd ed - S. Russell, P. Norvig (Prentice-Hall, 2010) WW • Chapter No.1

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