FQ17 CS 171 LEC A: INTRO ARTIFCL INTEL (34210)

Course Syllabus

FQ17 CS171: Introduction to Artificial Intelligence

Prof. Richard Lathrop

(Current content and syllabus draw upon previous offerings by

Profs. Lathrop, Ihler, Smyth, Mjolsness, Kask, and Dechter)



 

Place, Time, Instructors:

Place: HIB 100 (building 610 on the UCI campus map)
Time:
Tuesday/Thursday 12:30-1:50pm
Discussion Sections:
Fridays, variable times, in ICS 174 (building 302 on the UCI campus map)

 

(If you send email, please put “CS-171” somewhere in the Subject line.)

Instructor: Richard Lathrop, <rickl@uci.edu>

Office hours Wednesday 2-3pm in DBH 4224, or anytime by appointment

Teaching Assistants:

Jia Chen, <jiac5@uci.edu>

(Dis 1 at 8am; Dis 2 at 10am; Office hours Thursday 9-10am in ICS 424F)

Sridevi Maharaj, <sridevi.m@uci.edu>

(Dis 3 at 1pm; Dis 4 at 2pm; Office hours Tuesday 5-6pm in DBH 4044)

Readers:

Kyoungwon Kim <wonkim@uci.edu>

(Office hours Tuesday 9-10am in ICS 424A; returns quizzes for last names A - H)

Zephyr Yao <zhihaoy1@uci.edu>

(Office hours Monday 9-10am in ICS 424F; returns quizzes for last names I - P)

Dongxu Zhao <dongxuz1@uci.edu>

(Office hours Friday 9-10am in ICS 424F; returns quizzes for last names Q - Z)

Coding Project: Abdullah Younis <younisa@uci.edu>

Project Clinic: Wednesdays, 8pm, in Rowland Hall room 104 (building 400 on the UCI campus map)

(If you send email, please put “CS-171” somewhere in the Subject line.


Goal:

The goal of this class is to familiarize you with the basic principles of artificial intelligence. This is a

rize you with the basic principles of artificial intelligence. This is a

The goal of this class is to familiarize you with the basic principles of artificial intelligence. This is a broad introductory survey course. You will learn some basic AI techniques, the problems for which they are applicable, and their limitations.

The course content is organized roughly around what often are considered to be three central pillars of AI: Search, Logic, and Learning. Topics covered include basic search, heuristic search, game search, constraint satisfaction, knowledge representation, logic and inference, probabilistic modeling, and machine learning algorithms.

The Order of Topics will follow roughly your Russell&Norvig textbook (see textbook details below), although lecture and course content sometimes will include other important content not in your text:

Introduction, viewpoints about AI, agents (Ch. 1, 2)

Agents and problem formulations (Ch. 1, 2, 3)

Uninformed search (Ch. 3)

Informed search (Ch. 4)

Game playing (Ch. 5)

Constraint satisfaction (Ch. 6)

Propositional logic (Ch. 7)

Midterm Exam

First Order Logic (Ch. 8)

Inference and Knowledge Representation in First Order Logic (Ch. 9)

Uncertainty, Probability, Bayesian Networks (Ch. 13, 14)

Machine Learning from observations (Ch. 18)

Clustering, Regression, Statistical learning (Ch. 20)

Coding Project Due

Final Exam


Class Setup:

The course will be primarily lecture-based. There will be a Mid-term and a Final Exam. On every other Thursday before the Mid-term Exam, and every other Tuesday after it, the first 20 minutes will be an in-class pop quiz, followed by lecture (see specific dates calendar, below). The frequent quizzes are intended to encourage you to stay current with the course material. All exams and quizzes may cover all material presented in class, including lectures and assigned textbook reading. Quizzes will cover mostly material presented since the last quiz, and also may include questions that many students missed on the previous quiz. The Final Exam will cover mostly material since the Mid-term Exam, and also will include many questions intended to encourage you to remember the earlier material (i.e., the Final Exam will be comprehensive). Please study the previous CS-171 quizzes and exams (Files::Past Exams), which are made available as study guides to help you learn and master the class material; they are important guides about the performance that will be expected from you now.

We will use Canvas Discussions for questions and discussion.  Please post your questions and comments there.

The best way to answer your questions is to ask them in Discussion Section. If you are confused about something then many other students are also, so asking questions in Discussion Section will benefit both you and many of your fellows.


Homework:

Homework will be assigned, but is not graded. The reason is that prior student course evaluations alerted me to the existence of student cheating by way of copying the homework answers. I deplore this degree of personal degradation in dishonest students, but I cannot control it, and so I avoid the opportunity. I remain determined to create a fair and honest educational experience for all students, as best I can.


Course Coding Project:

The coding project is now available on Github:

https://github.com/riyt/Wumpus_World_Student

 

There will be an AI coding project (see the Project details page, TBA). This is an individual or pair project, i.e., you must do it entirely by yourself or form a team of two people. Sometimes teams do not work out. Any team member may dissolve their team at any time by so notifying the Instructor, TAs, and Tournament Director. Any code written before the dissolution is “community property” which may be used freely by both former team members. Any code written after the dissolution is the sole property of the person who wrote it.

Please note that you are encouraged to discuss concepts, methods, algorithms, etc.; but you are forbidden to copy: (1) source code from any source, although you are allowed to include standard libraries provided by the environment or compilation environment; or (2) text from any source unless properly cited and set off as a quote. Except for standard libraries and class materials provided from this class website, you or your team must invent and write all of your own code by yourself. Except for properly referenced material, you or your team must write all of your own project report by yourself.

Please note that your source code and project report are subject to analysis by automated plagiarism detection programs, and that direct copying will be treated as an act of academic dishonesty (please see the section on “Academic Honesty” below).

Please start your AI coding project earlier than you believe necessary, i.e., immediately. It will take longer and be more difficult than you expect (as is true of all coding projects everywhere at all times).

For your project report, please write a short (~2 page) description using the provided template (TBA).

All the various CS-171 AI project shells were written by former CS-171 students who became interested in AI and signed up for CS-199 in order to pursue their interest and write more interesting AI project shells. Please let me know if this is of interest to you (CS-171 grade of A- or better required).


Textbook:

Required: Russell & Norvig : Artificial Intelligence; A Modern Approach, 3rd edition.

The course is based on, and the UCI bookstore has, the 3rd edition. The assigned textbook reading is required, and is fair game for quizzes and exams. You place yourself at a distinct disadvantage if you do not have the textbook. I expect that you have a personal copy of the textbook, and quizzes and exams are written accordingly.

Please purchase or rent your own personal textbook for the quarter (and then resell it back to the UCI Bookstore at the end if you don't want it for reference). Please do not jeopardize your precious educational experience with the false economy of trying to save a few dollars by not having a personal copy of the textbook.

Also, for your convenience, I have requested that a copy of the textbook be placed on reserve in the UCI Science Library. There is a two-hour check-out limit. However, please understand that with high student enrollments, it is unrealistic to expect that these thin reserves always will be available when you need them. Please purchase or rent your own personal textbook. Otherwise, you are at a severe disadvantage.

I do deplore the high cost of modern textbooks. You may find the textbook cheaper if you look online at sites such as eBay.com, Amazon.com, etc.; or search the web for other sites related to the textbook.


Grading:

Your grade will be based on Discussion Section participation (10%), a coding project (20%), the four quizzes (20%), a mid-term exam (25%), and a final exam (25%). Homework is assigned but ungraded.

Discussion Section is REQUIRED and roll will be taken each period (10 periods = 1 period per week over 10 weeks)  .However, 3 periods are "free" (i.e., to obtain full credit, you must attend at least 7 of the 10 weeks.)  You may not leave after roll has been taken and before the end of the period, i.e., it is not OK to show up for roll and then depart prematurely.

To get full credit for discussion attendance you must attend 7 Discussion Sections. Each week, discussion attendance is scored 1 if you attended and 0 if you did not.  You are automatically marked "Present" and scored 1 for the Veterans Day and Thanksgiving holidays, leaving you five Discussion sections that you must attend physically for full credit. Your 7 highest discussion attendance scores will be averaged, multiplied by 10% (the discussion attendance weight), and added to your total score.  Each Discussion Section attendance you miss below the required 7 will cost you 1/7 * 10% approx= 1.43% of your total score, unless excused by your TA for good cause and recorded as "Present" because excused.  In general, important professional events involving travel to distant cities, such as conferences, hackathons, and non-local job interviews, are sufficiently important to the student involved as to warrant an excused absence. (The student is required to provide full and complete documentation to your TA that supports your request, including copies of your confirmed travel itinerary.)  In contrast, minor local events, such as a local company lunch or a local job interview that easily could be switched to a different time, probably are less important than attending Discussion Section, and probably do not warrant an excuse.  In any case, your TA has sole authority to grant or not grant excused absences from Discussion Section.  Your TA's decision is final.

The Discussion Sections are an important part in the teacher training of your TAs as future professors.  As such, Discussion Sections are an important part of the UCI educational mission at the graduate student level.  If your smarts and motivation take you to graduate school someday, and you find that you yourself have become a TA, you then will appreciate how valuable this teacher training experience is to a TA who will become a future professor.  For this reason, Discussion Section attendance is required.

The AI coding project will be a “Wumpus World” AI agent (see Ch. 7 in R&N textbook). “Dumb” coding shells are available in C++, Java, and Python. You must write the “smarts.” This is a solo or pair project and you must do all of it all by yourself or with a single team-mate.

You are already behind schedule. Start coding now. More details below in the Project section. Your Project is divided into several Assignments, weighted as shown on the Assignments page to total 100 points for the Project. For each Assignment, you will lose 10% of your grade for that Assignment for every day or fraction thereof that Assignment submission is late. Your “Final AI” will be entered into a tournament against all of your classmate’s Final AIs. The top 10% will have their Project score increased by 10% (= 2% of total grade), the second 10% by 9% (= 1.8% of total grade), the third 10% by 8% (= 1.6% of total grade), and so on.

Quizzes will be given the first 20 minutes of class every second Thursday before, and each second Tuesday after, the Mid-term Exam (dates are listed in the Syllabus Overview below), and are closed-book, closed-notes. Your lowest quiz score will be discarded in computing your grade. It is not possible to make-up missed quizzes, but one missed quiz may be discarded as your lowest quiz score.

The mid-term exam will be given in class on Tuesday, 7 Nov., and is closed-book, closed-notes. It is not possible to make-up a missed Mid-term exam.

The final exam will be given in class on Friday, 15 Dec., 10:30-12:30am, and is closed-book, closed-notes. The Final exam will cover all course material from the entire quarter, with emphasis on the second half. It is not possible to make-up a missed Final exam.

I honor all requests made by the UCI Disability Services Center.
Also, I make exceptions for:

genuine medical conditions (I require a signed note from your doctor on official letterhead or equivalent documentation, e.g., a scanned copy of official hospital discharge papers),

births/deaths in the family (I require a copy of the birth/death certificate or equivalent documentation, e.g., a scanned copy of official funeral papers),

jury duty or other court proceedings (I require a copy of your jury service papers or other official court documents), or

field maneuvers of the US military or National Guard (I require a copy of your official orders).

Every student who fills out a course evaluation for CS-171 will receive a bonus of 1% added to their final grade, free and clear, off the curve, simply a bonus.
EEE will return to me the names of students who fill out evaluations (but not the content, which remains anonymous), provided that enough students fill out evaluations so that anonymity is not compromised. I will add 1% free bonus to the final grade of each such named student.
Student course evaluations are very important to me for monitoring and improving the course content, and very important to UCI for evaluating our success at our educational mission. *Please* fill out your student course evaluations.


Study Habits:

This course is technical, rigorous, and demanding. You will be expected to learn and master a large body of technical material in a very short period of time. You must demonstrate your mastery by (1) accurate performance on frequent quizzes and exams, and (2) successful implementation of an AI coding project.

I deliberately treat you as adults who are responsible for your own educational decisions, and so Lecture is optional. Discussion Section is required and roll will be taken, because it is part of our educational mission to train our TAs to become future professors. Nevertheless, students who do not attend both Lecture and Discussion Section are at a serious disadvantage and do not succeed as well in this class.

Students who don't do the reading, don't attend Lectures, or spend Lectures and Discussion Section sleeping, on cell phones, surfing the Web, or on social media, are wasting their time and might as well be absent. Such students send me email messages to ask questions that already were covered thoroughly and in detail during Lecture and once again in Discussion Section. On quizzes and exams, they miss points that already have been covered thoroughly.

In stark contrast, students who work hard, over-study, and learn the material, tend to do very well indeed.

Your educational moments are precious, and your education now will be the single most important factor in your future career success or failure. Please, make the most of your precious educational moments now. Please, attend both Lecture and Discussion Section, pay attention, ask questions, and master the material.

The class will move very quickly. Please do not ever fall behind in the class material. Instead, study frequently and diligently. Please begin your AI coding project earlier than you believe necessary; it will take longer and be more difficult than you expect (as is true of all coding projects everywhere at all times).

Please work harder and study longer. Please understand thoroughly all class material, and ask questions when you do not understand. Please attend all lectures and discussion sections. Please come to lectures and discussion sections prepared with questions about any material that is not clear. Please do all assigned reading, both before and again after lecture. Please review the lecture notes, several times over, both before and again after lecture, until you understand every detail. Please regularly attend office hours with me and the TA. Please ask questions about any class material that is not absolutely crystal clear.

Please work and understand all past quizzes and exams; they are important guides about the performance that will be expected from you now. Please work and understand all the optional homework.

Please OVERSTUDY!!


Team Formation project deadline is subject to change, TBA.

Week

Date

Event

Comments

1

Thu 28 Sep

Lecture

 Class setup, Intro Agents (Slides)

R&N Ch 1-2

Cultural Interest

 

Fri 23 Sep

No Discussion

Take a long weekend!

 

2

Tue 3 Oct

Lecture

Intro State Space Search (Slides)

Uninformed Search (Slides)

R&N 3.1-3.4

Cultural Interest

 

Thu 5 Oct

Lecture

Heuristic Search (Slides)

R&N 3.5-3.7

 

Fri 6 Oct

Discussion

Review, questions, optional HW #1

3

Tue 10 Oct

Lecture

Local Search (Slides)

R&N 4.1-4.2

Cultural Interest

 

Thu 12 Oct

Quiz #1 (quiz; key)

Lecture

Game (Adversarial) Search A (Slides)

R&N 5.1, 5.2, 5.4

 

Fri 13 Oct

Discussion

Review, questions, optional HW #2

4

Tue 17 Oct

Lecture

UCI Blood Donor Center presentation

Game (Adversarial) Search B (for slides see Game Search A)

R&N 5.3 (optional: 5.5+)

Cultural Interest

 

Wed 18 Oct

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 19 Oct

Constraint Satisfaction A (Slides)

R&N 6.1-6.4, except 6.3.3

 

Fri 20 Oct

Discussion

Review, questions, optional HW #3

5

Tue 24 Oct

Lecture

Constraint Satisfaction B (Slides)

R&N 6.1-6.4, except 6.3.3

Cultural Interest

 

Wed 25 Oct

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 26 Oct

Quiz #2 (quiz; key)

Lecture

Propositional Logic A (Slides)

R&N 7.1-7.4

 

Fri 27 Oct

Discussion

Review, questions, optional HW #4

6

Mon 30 Oct

Team Formation deadline

Minimal AI deadline

Your team name must consist only of alpha-numeric characters (0-9, a-z, A-Z) plus optional hyphens (dashes "-").

Minimal AI must run on openlab.ics.uci.edu in the Wumpus shell, make at least one intelligent move when started (not just climb out at once), and score >= -10 on average across many random caves

Tue 31 Oct

Lecture

Happy Halloween!

Propositional Logic B (Slides)

R&N 7.5 (optional: 7.6-7.8)

Cultural Interest

 

Wed 1 Nov

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 2 Nov

Lecture

Mid-term Exam Review (Slides)

Guest lecture by Sridevi Maharaj

All of above

 

Fri 3 Nov

Discussion

Review, questions, optional HW #5

7

Tue 7 Nov

Mid-term Exam (exam; key)

Mid-term Exam

All of above

Cultural Interest

 

Wed 8 Nov

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 9 Nov

Lecture

Predicate Logic Syntax (Slides)

R&N 8.1-8.5

 

Fri 10 Nov

Holiday!

Happy Veterans Day Holiday!

Vets, thank you for your service.  We are here because you were there.

8

Tue 14 Nov

Lecture

Predicate Logic Semantics/Inference (Slides)

Predicate Logic Knowledge Engineering (Slides)

Review R&N 8.3-8.5, Read 9.1-9.2 (optional: 9.5)

Cultural Interest

 

Wed 15 Nov

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 16 Nov

Lecture

Probability, Uncertainty (Slides)

R&N Ch 13, 14.1-14.5

 

Fri 17 Nov

Discussion

Review, questions

9

Tue 21 Nov

Quiz #3 (quiz; key)

Lecture

Bayesian Networks (Slides)

R&N Ch 18.1-18.4

Cultural Interest

 

Wed 22 Nov

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Wed 22 Nov

Draft AI deadline

Draft AI must run on openlab.ics.uci.edu, and score >= 100 on average across many random caves

 

Thu 23 Nov

Holiday!

Happy Thanksgiving Holiday!

 

 

Fri 24 Nov

Holiday!

Happy Thanksgiving Holiday!

10

Tue 28 Nov

Lecture

Intro Machine Learning (Slides)

R&N Ch 18.6.1-2, 20.3.1

Cultural Interest

 

Wed 29 Nov

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 30 Nov

Lecture

FOR INTERESTED STUDENTS

OPTIONAL MATERIAL

WILL NOT BE ON TESTS

Machine Learning Classifiers (Slides)

WILL NOT BE ON TESTS

R&N Ch 18.5-12, 20.1-2

 

Fri 1 Dec

Discussion

Review, questions

 

11

Tue 5 Dec

Quiz #4 (quiz; key)

Lecture

Special Topics Lecture: AlphaGo (Slides)

Guest lecture by Jia Chen

TBA

 

Wed 6 Dec

Project Clinic

Coding Project Clinic, 8pm, Rowland Hall 104

 

 

Thu 7 Dec

Lecture

Final Exam Review (Slides)

All of the above

 

Thu 7 Dec

Final AI Deadline (report template)

Final AI must run on openlab.ics.uci.edu, score >= 200 on average across many random caves, and be your best and final AI that will compete for you in the tournament.

Let the Games begin!

 

Fri 8 Dec

Discussion

Review, questions

12

Fri 15 Dec

Final Exam (exam; key)

10:30am-12:30pm --- NOTE DIFFERENT TIME

All of the above

 


Academic Honesty:

Academic dishonesty is unacceptable and will not be tolerated at the University of California, Irvine. It is the responsibility of each student to be familiar with UCI's current academic honesty policies. Please take the time to read the current UCI Academic Senate Policy On Academic Integrity and the ICS School Policy on Academic Honesty.

The policies in these documents will be adhered to scrupulously. Any student who engages in cheating, forgery, dishonest conduct, plagiarism, or collusion in dishonest activities, will receive an academic evaluation of "F" for the entire course, with a letter of explanation to the student's permanent file. The ICS Student Affairs Office will be involved at every step of the process.  We seek to create a level playing field for all students.

 

 

Course Summary:

Date Details Due