Introduction to Artificial Intelligence - Software Practice | CS 3500, Assignments of Computer Science

Download Introduction to Artificial Intelligence - Software Practice | CS 3500 and more Assignments Computer Science in PDF only on Docsity! CS 5300: Introduction to AISlide 1 Hal Daumé III (hal@cs.utah.edu) Introduction to AI CS 5300 / CS 6300 Artificial Intelligence Spring 2009 Hal Daumé III hal@cs.utah.edu www.cs.utah.edu/~hal/courses/2009S_AI CS 5300: Introduction to AISlide 3 Hal Daumé III (hal@cs.utah.edu) Course Details
Book: Russell and Norvig, AI: A Modern Approach Second Edition (the green one)
Prerequisites:
CS 3500: There will be a lot of programming
CS 2000: There will be a lot of probability

Work and grading:
Ten short written assignments (10% of grade)
May work in groups, but must write-up alone
Graded pass/fail, no late submissions
Five programming projects (35% of grade)
Must work in groups of two or three
Late < 2 days at 50% penalty, may be late only twice
Midterm (20%) and Final (35%) CS 5300: Introduction to AISlide 4 Hal Daumé III (hal@cs.utah.edu) Announcements
Very important stuff:
HW0 due Thursday!
P0 (Python tutorial) due next Tuesday!
Subscribe to mailing list/RSS feed now!
Python lab Friday (1pm-4pm) in CADE lab
Scott or I will be there the entire time
Class is full...
If you're going to drop, please drop soon
If you need a spot, please wait for someone to drop
Questions? CS 5300: Introduction to AISlide 5 Hal Daumé III (hal@cs.utah.edu) Our “sister” course
Berkeley, CS 188 taught by John DeNero:
http://inst.eecs.berkeley.edu/~cs188/sp09/information.html
Thanks to John and Dan Klein for sharing all their work!
Courses are ~90% identical
Both culminate roughly simultaneously in a Pacman “capture the flag” competition
We will run cross-university Pacman servers
They've run a similar course for ~3 years
Their class is about 2x as big
Special prizes for anyone who beats Berkeley! (CTF demo) CS 5300: Introduction to AISlide 6 Hal Daumé III (hal@cs.utah.edu) Today
What is AI?
Brief history of AI
What can AI do?
What is this course? CS 5300: Introduction to AISlide 7 Hal Daumé III (hal@cs.utah.edu) Sci-Fi AI? CS 5300: Introduction to AISlide 8 Hal Daumé III (hal@cs.utah.edu) What is AI? Think like humans Think rationally Act like humans Act rationally The science of making machines that: CS 5300: Introduction to AISlide 9 Hal Daumé III (hal@cs.utah.edu) Acting Like Humans?
Turing (1950) “Computing machinery and intelligence”
“Can machines think?” → “Can machines behave intelligently?”
Operational test for intelligent behavior: the Imitation Game
Predicted by 2000, a 30% chance of fooling a lay person for 5 minutes
Anticipated all major arguments against AI in following 50 years
Suggested major components of AI: knowledge, reasoning, language understanding, learning
Problem: Turing test is not reproducible or amenable to mathematical analysis CS 5300: Introduction to AISlide 10 Hal Daumé III (hal@cs.utah.edu) Thinking Like Humans?
The cognitive science approach:
1960s ``cognitive revolution'': information-processing psychology replaced prevailing orthodoxy of behaviorism
Scientific theories of internal activities of the brain
What level of abstraction? “Knowledge'' or “circuits”?
Cognitive science: Predicting and testing behavior of human subjects (top-down)
Cognitive neuroscience: Direct identification from neurological data (bottom-up)
Both approaches now distinct from AI
Both share with AI the following characteristic: The available theories do not explain (or engender) anything resembling human-level general intelligence
Hence, all three fields share one principal direction! Images from Oxford fMRI center CS 5300: Introduction to AISlide 12 Hal Daumé III (hal@cs.utah.edu) Acting Rationally
Rational behavior: doing the “right thing”
The right thing: that which is expected to maximize goal achievement, given the available information
Doesn't necessarily involve thinking, e.g., blinking
Thinking can be in the service of rational action
Entirely dependent on goals!
Irrational insane, irrationality is sub-optimal action≠
Rational successful≠
Our focus here: rational agents
Systems which make the best possible decisions given goals, evidence, and constraints
In the real world, usually lots of uncertainty
… and lots of complexity
Usually, we’re just approximating rationality
“Computational rationality” a better title for this course