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COMP 3009 Introduction to AI Dr Eleni Mangina

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1 COMP 3009 Introduction to AI Dr Eleni Mangina

2 TEXTBOOK “Artificial Intelligence” Structures and Strategies for Complex Problem Solving George F. Lugger & William A. Stubblefield

3 ARTIFICIAL INTELLIGENCE “Artificial Intelligence (AI) may be defined as a branch of computer science that is concerned with the automation of intelligent behavior” WHAT IS INTELLIGENCE? -Is it a single characteristic? OR… -Is it a collection of distinct and related abilities? -Is it learned OR… is it a priori existence?


5 QUESTIONS: Is it necessary to pattern an intelligent computer program after what is known about human intelligence OR is a strict “engineering” approach to the problem sufficient? Is it even possible to achieve intelligence on a computer OR does an intelligent entity require the richness of sensation and experience that might be found only in a biological existence? DID YOU GET CONFUSED? DO NOT WORRY! AI offers a unique and powerful tool for exploring exactly these questions!!

6 “Artificial Intelligence is the science that investigates human intelligence by trying to build it in artificial” Let’s talk about it!!

7 HISTORY Aristotle: “most fascinating aspect of nature is: change”, philosophy of nature = study of things that change  Philosophical basis for: Symbolic computing and data abstraction LOGIC = the “instrument”(organon) Study of thought itself at the basis of all knowledge! Propositions  true OR false P: “all men are mortal” Q: “Socrates is a man” “Socrates is mortal” Deductive form  modus ponens

8 HISTORY (cont.) Renaissance: Thinking about humanity and its relations to the natural world. Empiricism  understanding nature Scientists and philosophers realized that thought itself, the way that knowledge was represented and manipulated in the human mind, was a difficult but ESSENTIAL subject for scientific study!

9 HISTORY (cont.) Copernican: Ancient Earth centered model  Rotates around the sun Our ideas about the world were seen as fundamentally distinct from its appearance! Galileo: His scientific observations further contradicted the “obvious”truths about the natural world and whose development of mathematics as a tool for describing that world emphasized the distinction between our ideas about the world and the world it self! Descartes: Cognitive introspection “Cogito ergo sum” = I think, therefore I am!!

10 THE TURING TEST 1950: British Mathematician Alan Turing MACHINE INTELLIGENCE Question: Can a machine actually think? interrogator

11 Turing test (cont.) Measures the performance of an allegedly intelligent machine against that of a human being. Turing called the “imitation game” places the machine and a human counterpart in rooms apart from a second human being, referred to as the “interrogator”. The interrogator is not able to see or speak directly to either of them, does not know which entity is actually the machine and may communicate with them solely by the use of a textual device such as a terminal. The interrogator is asked to distinguish the computer from the human being solely on the basis of their answers and questions asked over their device!

12 Turing test (cont.) If the interrogator cannot distinguish the machine from the human then, Turing argues that the machine may be assumed to be intelligent! The important features of this test are: 1.It gives us an objective notion of intelligence 2.It prevents us from being sidetracked by such confusing and currently unanswerable questions as whether or not the computer uses the appropriate internal process or whether or not the machine is actually conscious of its actions! 3.It eliminates any bias in favor of living organisms by forcing the interrogator to focus solely on the content of the answers to questions

13 Turing test (cont.) Turing test has been used to evaluate many AI programs BUT there have been some criticisms: 1.It does not test abilities requiring perceptual skill or manual dexterity (important components of human intelligence) 2.Constrains machine intelligence to fit a human DO WE REALLY WISH A MACHINE TO DO MATHEMATICS AS SLOWLY AND INACCURATELY AS A HUMAN?

14 AI Application areas Game playing Automated reasoning and Theorem proving Expert Systems Natural Language Understanding and Semantic Modeling Modeling Human Performance Planning and Robotics Languages and Environments for AI Machine Learning Emergent Computation

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