Transcript pptx - Williams College Computer Science

CSCI 373: Artificial Intelligence
Andrea Danyluk
September 6, 2013
• Who are you?
– Roster
“Artificial Intelligence”
• First thing that comes to mind?
• What is “intelligence”?
– According to Merriam-Webster:
• The ability to learn or understand or to deal with new or
trying situations: the skilled use of reason
• The ability to apply knowledge to manipulate one’s
environment or to think abstractly as measured by objective
criteria (as tests)
• What
[abilities]
involve?
Typically
derivedoes
fromintelligence
our understanding
of the
–
–
–
–
–
Ability most
to learn
intelligent entities we know:
Ability to reason Ourselves.
Ability to apply “knowledge”
Ability to think abstractly
Ability to demonstrate the above skills by
• Taking in percepts
• Acting (physically or otherwise)
What is AI?
The science of making machines that
Think Humanly
Think Rationally
Act Humanly
Act Rationally
[CS 188 UC Berkeley]
Rationality
• An ideal performance measure; does a system
do the “right thing” given what it knows?
• Involves a combination of mathematics and
engineering.
Goals of “Computational Rationality”
• Engineering
– To solve real-world problems
– To build systems that exhibit rational behavior
• Scientific
– To understand what kind of computational
mechanisms are needed for modeling rational
behavior
Logistics
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Where/When: Here (TPL 114) on MWF at 10am
Prof: Me (Andrea Danyluk)
Email: [email protected]
Phone: x2178
Office: TCL 305
Office Hours: Pretty much any time my office
door is open. And Mon 1:30-3:30, Tues 1:302:30, Thurs 1-2
• 373 website:
www.cs.williams.edu/~andrea/cs373
What we’ll cover
• Making Decisions
– Fast search/planning/problem solving
– Adversarial search
– Constraint satisfaction
• Reasoning under uncertainty
– Bayes’ nets
– Decision theory
• Logic
• Learning
– Reinforcement learning
– A bit of supervised classifier learning
Work and grading
• Programming assignments (50%)
– One tutorial plus five more
– Python
– Teamwork (required, except for tutorial)
– Autograding + code review
– “The Pacman Assignments”
– Do not – absolutely not – post solutions to any
part of these assignments!
Work and grading
• Project (25%+10%)
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Topic of your choice (with my sign-off)
Short written proposal
Python or Java (some exceptions allowed)
Deliverables
• code+demo+presentation (25%)
• Paper (10%)
• One exam (10%)
– Short take-home
• Other (5%)
– Short response papers
– Being here, being engaged, being prepared….
Due dates and lateness
• Pacman/machine learning assignments
– Up to 4 free late days (can use at most 2 at once)
• Project code+demo+presentation
– 10% late penalty per day
• Paper responses and final paper
– Must be submitted on time
Honor Code
• Exam: follow the College Honor Code. The
work on the exam must be your own work.
• Assignments:
– Listen carefully
– Read the Honor Code Guidelines in the syllabus
– When in doubt, ask me
What can AI do?
• Play a decent game of chess?
– Play a decent game of Jeopardy?
• Ambiguity of language
– After Governor Baldridge watched the lion perform, he was
taken to Main Street and fed twenty-five pounds of red meat
in front of the Fox Theater.
– Dr. Benjamin Porter visited the school yesterday and lectured
on"Destructive Pests". A large number were present.
– Play a decent game of table tennis?
– Play a decent game of soccer?
• What the robot sees
[Adapted from Russell]
What can AI do?
• Drive safely at high speed?
– Drive safely in an urban setting?
• Schedule and manage a fleet of luxury limousines
for business travelers for one of the largest travel
agencies in Hong Kong?
• Assist in making grad school admission decisions?
• Identify disease outbreaks?
• Monitor prescriptions?
What can AI do?
• Write a news brief?
• Be a punster?
– “What do you call a spicy missile? A hot shot!”
– What is the difference between leaves and a car?
One you brush and rake, the other you rush and
brake.