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Introduction to Artificial Intelligence Prof. Kathleen McKeown 722 CEPSR Tas: Andrew Rosenberg Speech Lab, 7 th Floor CEPSR Sowmya Vishwanath TA Room.

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Presentation on theme: "Introduction to Artificial Intelligence Prof. Kathleen McKeown 722 CEPSR Tas: Andrew Rosenberg Speech Lab, 7 th Floor CEPSR Sowmya Vishwanath TA Room."— Presentation transcript:

1 Introduction to Artificial Intelligence Prof. Kathleen McKeown 722 CEPSR Tas: Andrew Rosenberg Speech Lab, 7 th Floor CEPSR Sowmya Vishwanath TA Room

2 2 What is artificial intelligence? Building systems that exhibit intelligent behavior Excitement

3 3 2001

4 4 Definitions Systems that think like humans Systems that think rationally The exciting new effort to make computers think.. Machines with minds, in the full and literal sense (Haugeland, 1985) The study of the computations that make it possible to to perceive, reason and think. (Winston 1992) Systems that act like humans Systems that act rationally The art of creating machines that perform functions that require intelligence when performed by people. (Kurzweil 1990) Computational intelligence is the study of the design of intelligent agents. (Poole et al. 1998)

5 5 Systems that think like humans versus Systems that act like humans

6 6 Systems that think rationally versus Systems that act rationally

7 7 Class focus Systems that act Like humans Rationally

8 8 AI is a smorgasbord of topics Core areas Knowledge representation Reasoning/inference Machine learning Perception Vision Natural language Robotics Uncertainty Probabilistic approaches General algorithms Search Planning Constraint satisfaction Applications Game playing AI and education Distributed agents Decision theory Electronic commerce Auctions Reasoning with symbolic data

9 9 AI is a smorgasbord of topics Core areas Knowledge representation Reasoning/inference Machine learning Perception Vision Natural language Robotics Uncertainty Probabilistic approaches General algorithms Search Planning Constraint satisfaction Applications Game playing AI and education Distributed agents Decision theory Electronic commerce Auctions Reasoning with symbolic data

10 10 AI used to be Expert systems Medical expert systems – diagnosis Computer systems design Theorem proving/software verification Inheritance, class-based systems

11 11 AI is interdisciplinary Psychology Cognitive Science Linguistics Neuroscience Economics Philosophy Physics

12 12 What will we study in the course?

13 13 Assignments Evaluation of a practical AI system 2 programming assignments Search (2 weeks) Game playing (4 weeks) 1 programming plus paper (2 weeks) 2 written assignments (1 week each)

14 14 Grading 45% homeworks – homeworks are important. You can’t pass without doing them. 5% class participation Notes will be posted on the web There will be board work in addition to slides. The slides don’t tell the whole story. Class is a social experience – there will be discussion 20% midterm 30% final

15 15 Reading Chapters from the required text: Artificial Intelligence: A Modern Approach, Russell and Norvig, 2003. Papyrus Bookstore. Selected papers. Watch for papers on reserve. Will be posted on the Reading Section of the web

16 16 Some Examples Natural language processing Question answering on the web Spoken language dialog meets the real world Robotics Robocup soccer Roomba: robotics meets the real world Mars Rover Vision Modeling the real world

17 17 Machine Learning Learning to play pool Learning to recognize objects


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