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Great Ideas in Computer Science - Artificial Intelligence and Knowledge Representation

Join Dr. Carl Alphonce for an enlightening lecture on AI, reasoning, and knowledge representation. Learn about explicit and implicit knowledge, reasoning, and rule of inference. Explore how to answer questions and develop predicates for events.

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Great Ideas in Computer Science - Artificial Intelligence and Knowledge Representation

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  1. CSE111: Great Ideas in Computer Science Dr. Carl Alphonce 219 Bell Hall Office hours: M-F 11:00-11:50 645-4739 alphonce@buffalo.edu

  2. cell phones off (please)

  3. Announcements • HW5 • Part 1 – work on this week • Part 2 – work on next week • due April 16 • 4/5-4/9: Artificial Intelligence • 4/12-4/16: Theory • 4/19-4/23: Exam week

  4. Today’s Agenda • Artificial Intelligence • Knowledge representation and reasoning • Game playing

  5. Reasoning • Making implicit knowledge explicit • Traditional example: • All men are mortal. • Socrates is a man. • Socrates is mortal. Explicit knowledge Rule of inference Implicit knowledge

  6. Knowledge representationfor reasoning • Represent knowledge so reasoning is supported • How should we represent “Maharani serves vegetarian food”? • Serves(Maharani, VegetarianFood)

  7. Answering questions • Does Maharani serve vegetarian food? • What if we knew only: • VegetarianRestaurant(Maharani)

  8. Inference • Add rule: • All(X) VegetarianRestaurant(X) => Serves(X,VegetarianFood)

  9. Events • I ate • I ate a turkey sandwich • I ate a turkey sandwich at my desk • I ate at my desk • I ate lunch • I ate a turkey sandwich for lunch • I ate a turkey sandwich for lunch at my desk

  10. Separate predicates? • Eating-1 • Eating-2 • Etc. • Will not support reasoning!

  11. Event reification • Exists(E) Eating(E) ^ Eater(E,speaker) ^ Eaten(E,turkeySandwich) ^ …

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