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Artificial Intelligence

Artificial Intelligence. What is it ?. Some Definitions. Herbert Simon: We call programs intelligent if they exhibit behaviors that would be regarded intelligent if they were exhibited by human beings.

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Artificial Intelligence

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  1. Artificial Intelligence What is it ?

  2. Some Definitions • Herbert Simon: We call programs intelligent if they exhibit behaviors that would be regarded intelligent if they were exhibited by human beings. • Elaine Rich: AI is the study of techniques for solving exponentially hard problems in polynomial time by exploiting knowledge about the problem domain. • Elaine Rich and Kevin Knight: AI is the study of how to make computers do things at which, at the moment, people are better.

  3. More • Stuart Russell and Peter Norvig: [AI] has to do with smart programs, so let's get on and write some. • Avron Barr and Edward Feigenbaum: Physicists ask what kind of place this universe is and seek to characterize its behavior systematically. Biologists ask what it means for a physical system to be living. We in AI wonder what kind of information-processing system can ask such questions. • Claudson Bornstein: AI is the science of common sense. • Douglas Baker: AI is the attempt to make computers do what people think computers cannot do. • Astro Teller: AI is the attempt to make computers do what they do in the movies.

  4. More • The goal of work in artificial intelligence is to build machines that perform tasks normally requiring human intelligence. (Nilsson, Nils J. (1971), Problem-Solving Methods in Artificial Intelligence (New York: McGraw-Hill): vii.) • Research scientists in Artificial Intelligence try to get machines to exhibit behavior that we call intelligent behavior when we observe it in human beings. (Slagle, James R. (1971), Artificial Intelligence: The Heuristic Programming Approach (New York: McGraw-Hill): 1.) • B. Raphael ... has suggested that AI is a collective name for problems which we do not yet know how to solve properly by computer. (Michie, Donald, "Formation and Execution of Plans by Machine," in N. V. Findler & B. Meltzer (eds.) (1971), Artificial Intelligence and Heuristic Programming (New York: American Elsevier): 101-124; quotation on p. 101.)

  5. Even More • What is or should be [AI researchers'] main scientific activity--studying the structure of information and the structure of problem solving processes independently of applications and independently of its realization in animals or humans. (McCarthy, John (1974), Review of "Artificial Intelligence: A General Survey," Artificial Intelligence 5: 317-322; quotation on p. 317.)

  6. More • Artificial intelligence is concerned with the attempt to develop complex computer programs that will be capable of performing difficult cognitive tasks. (Eysenck, Michael W. (1990), "Artificial Intelligence," in M.W. Eysenck (ed.), The Blackwell Dictionary of Cognitive Psychology (Oxford: Basil Blackwell): 22.)

  7. And Your Definition? • What do you think AI is in your own words.

  8. From last weeks discussion • We know AI has something to do with problem solving • It involves Knowledge • Reasoning and Learning and much much more.

  9. Obviously the next Question is • WHAT is Knowledge???????????

  10. Knowledge • Eolas • Is it Data • Is it Information • Is it something else

  11. What do you think?

  12. Data • Data, are basic facts – typically found in a database.

  13. Data • Turban and Aronson definition • “Data are a collection of facts, measurements and statistics.”

  14. Information • Information includes data • But also includes associations , relationships, semantics and so on

  15. Information • Turban and Aronson definition • “Information is defined as organized or processed data that are timely (i.e. inferences from the data are drawn within the time frame of applicability”

  16. Knowledge • ????????????????????

  17. What is knowledge ? • • What do people have inside their head when they know something ? • • Is knowledge expressed in words ? • • If so, how could one know things that are easier to do than to say, like • tying a shoestring or hitting a baseball ? • • If knowledge is not expressed in words, how can it be transmitted in • language ? • • How is knowledge related to the world ? • • What are the relationships between the external world, knowledge • in the head, and the language used to express knowledge about the • world ?

  18. Knowledge is more than a static encoding of facts, it also includes the ability to use those facts in interacting with the world. • Basic premise of AI is that knowledge of something is the ability to form a mental model that accurately represents the thing as well as the actions than can be performed by it and on it. • By testing actions on the model, a person (or robot) can predict what is likely to happen in the real world.

  19. Knowledge • knowledge is information that can be applied for a specific and useful purpose • Knowledge is that which we know. • Knowledge – Facts – Concepts- Procedures- How- To – Associations- Analogy-Rules of Thumb-Objects- Classifications-Meta Knowledge- Something to be learned

  20. Definitions of Knowledge “Dictionary Definition” • The state or fact of knowing. • Familiarity, awareness, or understanding gained through experience or study. • The sum or range of what has been perceived, discovered, or learned.

  21. More of the definition • Learning; erudition: teachers of great knowledge. • Specific information about something. • Carnal knowledge.

  22. Physical Symbol Hypothesis of Knowledge • The prevailing epistemology is the physical symbol hypothesis of Newell and Simon (1981). • Essentially this hypothesis considers that knowledge consists of symbols of reality and relationships between these symbols and that intelligence is the appropriate logical manipulation of the symbols and their relations. • Although Newell an Simon developed these ideas in the 50's as a basis for AI, they have a long and time honoured philosophical ancestry, through the early Wittgenstein, back through Descartes to Plato with his archetypes.

  23. Knowledge Principle • The extension of the physical symbol hypothesis is the "knowledge principle", that is, the success of an expert system does not depend on the sophistication of its inferencing or reasoning strategy, but on the amount of information it contains on how symbols are interrelated, that is the amount of knowledge it contains. (Feigenbaum 1977).

  24. Many Definitions • WIPO Secretariat made use of the following working concept of ‘traditional knowledge’ for the purposes of the fact-finding missions in1998-1999:

  25. ‘traditional knowledge’ … refer[s] to tradition based literary, artistic or scientific works; performances; inventions; scientific discoveries; designs; marks, names and symbols; undisclosed information; and all other tradition-based innovations and creations resulting from intellectual activity in the industrial, scientific, literary or artistic fields. “

  26. Big Issue • How do we get Knowledge into a computer • Knowledge Representation • And • How do we use it then - Inference

  27. Fundamental System Issues • A robust AI system must be able to store knowledge, apply that knowledge to the solution of problems, and acquire new knowledge through experience. • Among the challenges that face researchers in building AI systems, there are three that are fundamental: • knowledge representation, reasoning and searching, and learning.

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