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Welcome to CS 470/670 – Introduction to Artificial Intelligence Fall 2012

Welcome to CS 470/670 – Introduction to Artificial Intelligence Fall 2012. Instructor: Marc Pomplun. Instructor – Marc Pomplun. Office: S-3-171 Lab: S-3-135 Office Hours: Mondays 5:30pm – 7:00pm Wednesdays 4:00pm – 5:30pm

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Welcome to CS 470/670 – Introduction to Artificial Intelligence Fall 2012

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  1. Welcome toCS 470/670 – Introduction toArtificial IntelligenceFall 2012 Instructor: Marc Pomplun Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  2. Instructor – Marc Pomplun • Office: S-3-171 • Lab: S-3-135 • Office Hours: Mondays 5:30pm – 7:00pm Wednesdays 4:00pm – 5:30pm • Phone: 287-6443 (office) 287-6485 (lab) • E-Mail: marc@cs.umb.edu Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  3. The Visual Attention Lab Eye movement research Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  4. The new EyeLink-2K System Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  5. Example: Distribution of Visual Attention Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  6. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  7. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  8. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  9. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  10. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  11. Selectivity in Complex Scenes Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  12. Modeling of Brain Functions Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  13. Modeling of Brain Functions unit and connection l a y e r + 1 l in the interpretive network unit and connection in the gating network unit and connection in the top-down bias network l a y e r l l a y e r - 1 l Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  14. Computer Vision: Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  15. Human-Computer Interfaces: Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  16. Now back to CS 470/670: • Course Kit: • Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan Kaufmann 1998, ISBN 1-55860-467-7. • David M. Skapura, Building Neural Networks, Addison Wesley 1996, ISBN 0-201-53921-7 • On the Web: • http://www.cs.umb.edu/~marc/cs470/ • (contains all kinds of course information and also my slides in PPT, PDF and HTML formats, updated after each session) Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  17. Your Evaluation • 4 sets of exercises software projects: 25%non-programming questions: 10% • midterm (1.5 hours)25% • final exam (2.5 hours) 40% Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  18. Grading For the assignments, exams and your course grade, the following scheme will be used to convert percentages into letter grades: •  95%: A •  90%: A-  86%: B+ 82%: B 78%: B-  74%: C+  70%: C 66%: C-  62%: D+ 56%: D 50%: D-  50%: F Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  19. Complaints about Grading • If you think that the grading of your assignment or exam was unfair, • write down your complaint (handwriting is OK), • attach it to the assignment or exam, • and give it to me or put it in my mailbox. • I will re-grade the whole exam/assignment and return it to you in class. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  20. Artificial Intelligence (AI) Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  21. Natural Intelligence • Before we talk about “intelligent” machines, let us first consider examples of intelligence that we find in nature. • Of course there we will find many different levels of intelligence, cognitive abilities, and consciousness. • We will start with very basic abilities and make our way towards the highest forms of intelligence that are currently known to us. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  22. Viruses • not considered to be alive • do not reproduce on their own, but make bacteria produce copies of themselves • no learning in individual viruses; only “evolutionary learning” Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  23. Bacteria • are considered to be alive • reproduce by splitting up into two organisms • capable of some simple learning that allows them to move towards favorable environments Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  24. Insects • capable of learning and memorizing • primitive social interactions (trail of pheromones) • simple visual and olfactory perception (compound eyes) • coordinated movements of legs to master different types of terrains Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  25. Reptiles • good capability of vision (eyeballs, eye movements) • able to learn certain behaviors • hunting abilities • still very primitive social interactions Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  26. Higher Mammals • very powerful senses • produce sounds but no language • complex social interactions • probably consciousness and basic feelings that are related to our own Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  27. Non-Human Primates • very human-like genetic makeup and behaviors • produce different sounds with different meanings • capable of learning symbolic “language” • probably consciousness, self-awareness and basic feelings at the level of a human kid Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  28. Humans • complex social behaviors • able to learn high-level syntactic languages • extremely long phase of learning (upbringing) • consciousness, self-awareness, abstract thinking • awareness of past and future, planning capability Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  29. Robots (Current Stage) • built by humans • coordinated body movements • little learning capabilities • no real social interaction or language • no consciousness or self-awareness Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  30. Levels of Artificial Intelligence • Today’s computers can do many well-defined tasks (for example, arithmetic operations), much faster and more accurate than human beings. • However, the computers’ interaction with their environment is not very sophisticated yet. • How can we test whether a computer has reached the general intelligence level of a human being? • Turing Test: Can a computer convince a human interrogator that it is a human? • But before thinking of such advanced kinds of machines, we will start developing our own extremely simple “intelligent” machines. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  31. AI – The History • • AI is nearly as old as computing • • 1941 Konrad Zuse, Germany, general purpose computer • • 1943 Britain (Turing and others) Colossus, for decoding • • 1945 ENIAC, US. John von Neumann a consultant • • 1956 Dartmouth Conference organized by John McCarthy (inventor of LISP) • • The term Artificial Intelligence was coined at Dartmouth, which was intended as a two month study. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  32. AI – The Achievements • Robots make cars in all advanced countries. • • Reasonable machine translation is available for a large range of foreign web pages. • • Computers land 200 ton jumbo jets unaided every few minutes. • • Search systems like Google are not perfect but provide very effective information retrieval • • Robots cut slots for hip joints better than surgeons. • • The chess program Deep Blue beat world champoin Kasparov in 1997. • • Medical expert systems can outperform doctors in many areas of diagnosis. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  33. AI – A Comment • Despite all these achievements, one of the major philosophers of Cognitive Science wrote: • “… the failure of artificial intelligence to produce successful simulation of routine commonsense cognitive competences is notorious, not to say scandalous. We still don't have the fabled machine that can make breakfast without burning down the house; or the one that can translate everyday English into everyday Italian, or the one that can summarize texts..” (Jerry Fodor, The Mind doesn’t Work that Way, 2000, p.37). Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  34. What is Artificial Intelligence? • The use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular (Boden) • • The study of intelligence independent of its embodiment in humans, animals or machines (McCarthy) • • The pursuit of metaphysics by other means (Longuet-Higgins) • • AI is the study of how to do things which at the moment people do better (Rich & Knight) • • AI is the science of making machines do things that would require intelligence if done by men. (Minsky) Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  35. What is Artificial Intelligence? • One of major divisions in AI (and you can see it in the definitions on the previous slide) is between • Those who think AI is the only serious way of finding out how we work (since opening heads does not yet give much insight into this) and • • Those who want computers to do very smart things, independently of how we work. • This is the important distinction betweenCognitive Scientists vs. Engineers. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  36. Symbolism vs. Connectionism • There is another major division in the field of Artificial Intelligence: • Symbolic AI represents information through symbols and their relationships. Specific Algorithms are used to process these symbols to solve problems or deduce new knowledge. • Connectionist AI represents information in a distributed, less explicit form within a network. Biological processes underlying learning, task performance, and problem solving are imitated. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

  37. The Plan • In this course, we will first explore symbolic AI (the “traditional” approach) and then look at connectionist AI (artificial neural networks). • I will not be around next week, instead Nick Wang from my lab, a great AI expert, will teach you a lot of interesting things in the next two lectures. Introduction to Artificial Intelligence Lecture 1: What is Artificial Intelligence?

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