For the Final Exam, Perfect gives the percentage of students who received full credit, Partial gives the
percentage who received partial credit, and Zero gives the percentage who received zero credit.
(Due to rounding, etc., values below may be only appro

CS-171, Intro to A.I. Final Exam Winter Quarter, 2016
YOUR NAME:
YOUR ID:
ID TO RIGHT:
ROW:
SEAT:
The exam will begin on the next page. Please, do not turn the page until told.
When you are told to begin the exam, please check first to make sure that you

For the Mid-term Exam, Full credit gives the percentage who received 100%, Partial credit gives the
percentage who received partial credit, and Zero credit gives the percentage of students who received zero.
Problem 1:
full credit: ~15% (~12 students)
par

For the Final Exam, Perfect gives the percentage of students who received full credit, Partial gives the
percentage who received partial credit, and Zero gives the percentage who received zero credit.
(Due to rounding, etc., values below may be only appro

Below, for each problem on this Midterm Exam, Perfect is the
percentage of students who received full credit, Partial is the
percentage who received partial credit, and Zero is the percentage who
received zero credit.
(Due to rounding or other exceptional

CS171, Intro to A.I. Final Exam Summer Quarter, 2016
YOUR NAME:
YOUR ID:
ID TO RIGHT:
ROW:
SEAT NO.:
The exam will begin on the next page. Please, do not turn the page until told.
When you are told to begin the exam, please check first to make sure that y

Constraint sa*sfac*on problems II
CS171, Fall 2016
Introduc*on to Ar*cial Intelligence
Prof. Alexander Ihler
You Should Know
Node consistency, arc consistency, path consistency, Kconsistency (6.2)
Forward checking (6.3.2)
Local search for CS

Propositional Logic:
Methods of Proof (Part II)
You will be expected to know
Basic definitions
Inference, derive, sound, complete
Conjunctive Normal Form (CNF)
Convert a Boolean formula to CNF
Do a short resolution proof
Horn Clauses
Do a short for

Constraint sa*sfac*on problems
CS171, Fall 2016
Introduc*on to Ar*cial Intelligence
Prof. Alexander Ihler
Constraint Sa*sfac*on Problems
What is a CSP?
Finite set of variables, X1, X2, , Xn
Nonempty domain of possible values for each: D1, .,

Probability
CS171, Fall 2016
Introduc9on to Ar9cial Intelligence
Prof. Alexander Ihler
Reading: R&N Ch 13
Outline
Represen9ng uncertainty is useful in knowledge bases
Probability provides a coherent framework for uncertainty
Review of basic co

Chapter 2: Review of
Important Networking
Concepts
Magda El Zarki
Dept. of CS
UC Irvine
elzarki@uci.edu
http:/www.ics.uci.edu/~magda
1
Networking Fundamentals
Basic Internet technologies
Basic networking strategies
The Internet: A Collection of Networks