CompSci (CS) 171 — Introduction to Artificial Intelligence — Fall 2013


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           Current Announcements

            Place, Time, Instructor

            Goal

            Class Setup

            Textbook

            Grading

            Syllabus

                        Week 1

                        Week 2

                        Week 3

                        Week 4

                        Week 5

                        Week 6

                        Week 7

                        Week 8

                        Week 9

                        Week 10

                        Week 11

                        Project Due Date

                        Final Exam

            Project

            Study Guides --- Previous CS-171 Quizzes, Mid-term, and Final exams

            Online Resources

            Academic Honesty


Current Announcements:

 

·        The Final Exam answer key has been posted below and is available here.

·        The quiz #4 answer key has been posted below and is available here.

·        A revised project Specification has been posted to the class website with revised requirements of only (1) 9x9 sudoku, and (2) BT and FC only; extra credit will be given for extra effort.

·        As announced to the class mailing list, in support of students with weak coding skills the project requirements have been reduced to (1) 9x9 sudoku, and (2) BT and FC only.  Extra credit bonus points will be awarded to students who do more, and other changes have been made, as discussed in that email message.

·        If you are one of the students who have weak coding skills, I urge you to improve them.  I say this only with the best intentions of helping your future career.  The State of California pays me to give advice that benefits students.  It is highly unlikely that you will ever get a memo from your boss in industry that begins, “In support of employees with weak coding skills the project requirements have been reduced....”

·        The quiz #3 answer key has been posted below and is available here.

·        Sigh.  On Saturday, 16 Nov 2013, I now make the same offer as before:  I believe that I now have fixed all of the broken links below. Please notify me by email if you find a link that does not seem to work properly. One Bonus Point will be awarded for each broken or incorrect link found (or any other error in this website).

·        A preliminary coding project specification has been posted below and is available here. More details will follow shortly.

·        The Mid-term Exam answer key has been posted below, and is also available here.

·        I believe that I now have fixed all of the broken links below. Please notify me by email if you find a link that does not seem to work properly. One Bonus Point will be awarded for each broken or incorrect link found (or any other error in this website).

·        Apparently the website links are broken again. I do hate bad software. Thank you, Bill Gates. I will fix it as soon as I am able. Sigh.

·        Due to an unavoidable off-campus meeting, Dr. Lathrop’s office hours will end at 11:30am on Wednesday, 6 Nov. Please come to office hours on that date before 11:30am, or send email to schedule an appointment anytime.

·        I believe that I now have fixed all of the broken links below. Please notify me by email if you find a link that does not seem to work properly. One Bonus Point will be awarded for each broken or incorrect link found (or any other error in this website).

·        The Quiz #2 answer key has been posted below, and is also available here.

·        The website is temporarily broken and will be fixed shortly. Apologies for any inconvenience.

·        I have revised the class schedule and syllabus below to reflect the extra lecture that I gave on CSP in support of your coding project. Please note that Quiz #2 now will be given Tue., 29 Oct.; the Mid-term Exam now will be given Thu., 7 Nov.; and Quiz #3 now will be given Tue., 19 Nov. The dates of Quiz #4 and the Final Exam are unchanged. Please let me know if you notice any errors or problems.

·        Quizzes can be picked up during either discussion section, Will’s office hours on Mondays at 2, or Kartik's office hours on Fridays at 3.

·        As announced in lecture Thursday, due to the extra lecture that I gave on CSP in support of your coding project, the entire CS-171 schedule and syllabus will slip one class period.  As mentioned in lecture, this will consume the last class period on the current schedule (3 Dec.), now listed as "Special Topic." As a consequence, quizzes hereafter will be given on Tuesdays, not Thursdays, and the Mid-term date also will slip one class period. In particular, Quiz #2 now will be given Tue., 29 Oct.

·        Prof. Lathrop’s office hours for Weds, 16 Oct, are canceled due to the ICS Faculty Panel on Improving Your Grad School Application, which he is organizing and which you are urged to attend.

·        The Quiz #1 answer key has been posted below, and is also available here.

·        A preliminary guide to your Monster Sudoku project has been posted to the Project section, and is also available here.

·        Prof. Lathrop’s office hours on Wednesday, October 9, will end at noon due to a department faculty meeting that begins at noon.

·        A helpful student has contributed a link to a PDF of the course textbook:

            http://en.tjcities.com/wp-content/uploads/Books/Artificial_Intelligence_3rd.pdf

·        There are now  two CS-171 MessageBoard forums at EEE:

(1) Class Discussion; and

(2) Seeking project programming team partner.  (Please use this forum if you are seeking a programming team partner for the class project.)

 

·        Current announcements will appear here, at top-level, for quick and easy inspection.

 


Place, Time, Instructor:

 

Lecture:

Place: HG 1800 (Humanities Gateway; Building 611 on the UCI campus map)
Time: Tuesday/Thursday 2:00-3:20pm

Discussion sections:

Dis 1: Monday 1:00-1:50pm in SH 128 (Steinhaus Hall; Building 502 on the UCI campus map)

Dis 2: Wednesday 1:00-1:50pm in SH 128 (same as above)

 

Instructor: Richard Lathrop
Office hours: Wednesday 11:00am-12:20pm, or anytime by appointment, in DBH-4224

Email:  rickl@uci.edu

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

 

TA: Will Devanny
Office hours: Monday 2-3pm in DBH-3013, or anytime by appointment.

Email: wdevanny@uci.edu

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

 

Reader: Kartik Saxena
Office hours: Friday 3-4pm, or anytime by appointment, in DBH-2061.

Email: ksaxena@uci.edu

(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. 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 are often 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.


Class Setup:

The course will be primarily lecture-based.  There will be a Mid-term and a Final Exam.  On every second Thursday, the first 20 minutes will be an in-class pop quiz, followed by lecture.  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 some questions intended to encourage you to remember the earlier material.

There will be an AI coding project.  You are allowed to do the project by yourself, or you may form project teams of two students following the “Pair Programming” paradigm.  Please note that you are encouraged to discuss concepts, methods, algorithms, etc.; but you are forbidden to copy: (1) source code from any source, or (2) text from any source unless properly cited and set off as a quote.  Except for class materials provided from this class website, you must invent and write all of your own code by yourself with your partner.  Except for properly referenced material, you must write all of your project report by yourself with your partner. 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).

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.


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 will always be available when you need them.  Please purchase or rent your own personal textbook.

I do deplore the high cost of textbooks.  You are likely to find the book cheaper if you search online at EBay.com, Amazon.com, and related sites.

A student kindly contributed a link to a PDF of the course textbook:

            http://en.tjcities.com/wp-content/uploads/Books/Artificial_Intelligence_3rd.pdf

A student kindly contributed the following suggestion, for which I cannot vouch, and which I provide for your use if it is useful to you:

Hello,

I just wanted to point out that there does exist an international edition of the book which can be bought for around $40-50. I cannot comment on what specific differences there are for this particular book, though they are usually very small (exercises moved around, etc). Obviously, it is in paperback.

http://www.valorebooks.com/affiliate/buy/siteID=e79mzf/ISBN=0136042597

http://www.abebooks.com/servlet/BookDetailsPL?bi=4161131466&cm_ven=sws&cm_cat=sws&cm_pla=sws&cm_ite=4161131466&afn_sr=para&para_l=1

http://www.biblio.com/books/360025589.html

Personally I plan on using this book for a while so I bought the hardcover version, but I just wanted to point out that this is an option for those looking for a more 'economical' route.

~ XXXXXX [name anonymized to protect student privacy]


Grading:

Your grade will be based on the bi-weekly quizzes (20%), a project (20%), a mid-term exam (25%), and a final exam (35%).  Homework is assigned but ungraded.

·        Quizzes will be given the first 20 minutes of class on the dates listed in the syllabus below.  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 Thursday, November 7, and is closed-book, closed-notes.  It is not possible to make-up a missed mid-term exam.

·        The final exam will be given on Thursday, December 12, 1:30 - 3:30 p.m., and is closed-book, closed-notes.  The final exam will cover all course material from the entire quarter, but mostly the second half.  It is not possible to make-up a missed final exam.

            Dates and times for all final exams are set by the UCI Registrar (Final Exam Schedule 2013-14).

I make exceptions for genuine medical conditions (I require a note from your doctor on official letterhead) or deaths in the family (I require a copy of the death certificate).  Also, I honor all requests made by the UCI Disability Services Center.

·        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.

 

·        “Bonus Points” will be awarded, at my sole discretion, (1) to the first student who spots a genuine technical error (typos don’t count) in any of the course materials before I spot it too, and (2) for helpful contributions to the class as we go along.  One bonus point is equivalent to one quiz point.

 

            Your Bonus Points, if any, should be visible to you in EEE GradeBook. If for some reason you have been awarded a Bonus Point, but you did not get a notification from me or it did not appear in EEE GradeBook, please do not hesitate in emailing me as a reminder just to avoid an unlikely error.

 


Syllabus:

The following represents a preliminary syllabus. Some changes in the lecture sequence may occur due to earthquakes, fires, floods, wars, natural disasters, unnatural disasters, or the discretion of the instructor based on class progress.

Background Reading and Lecture Slides will be changed or revised as the class progresses at the discretion of the instructor.  Please note:  I may tweak or revise the lecture slides prior to the lecture; please ensure that you have the current version.

Please read the assigned textbook reading in advance of each lecture, then again after each lecture.


Week 1:

            Thu., 26 Sep., Introduction, Agents.

                        Read in Advance: Textbook Chapters 1-2.

                        Lecture slides: Introduction, Agents [PDF; PPT].


            Optional Cultural Interest:

                        IBM Watson: Final Jeopardy! and the Future of Watson

                        AI vs. AI. Two chatbots talking to each other.

            Optional Reading:

                        John McCarthy, “What Is Artificial Intelligence?

                                                HTML and other versions of “What is AI?”

            Optional URL:

Association for the Advancement of Artificial Intelligence (AAAI)

AAAI’s Student Resources

AAAI’s digital library of more than 10,000 AI technical papers

AAAI’s AI Magazine

AAAI’s Author Kit

                        John McCarthy Homepage

 

            Tue., 1 Oct., Uninformed Search.

                        Read in Advance: Textbook Chapter 3.1-3.4.

                        Lecture slides (three parts):

                                    (1) Introduction to Search [PDF; PPT]; and

                                    (2) Uninformed Search [PDF; PPT].


            Optional Cultural Interest:

                        Boston Dynamics Big Dog (new video March 2008)

                        Honda's robot ASIMO

Optional Reading:

            Newell & Simon’s “Symbols and Search” Turing Award Lecture (1976).

            Herbert Simon was awarded a Nobel Prize (in economics, 1978).

Week 2:

            Thu., 3 Oct., Heuristic Search.

                        Read in advance:  Textbook Chapter 3.5-3.7.

                        Lecture slides: Heuristic Search [PDF; PPT].

 

            Optional Cultural Interest:

                        Infinite Mario AI - Long Level

                        An attempt at a Mario AI using the A* path-finding algorithm.

                                    It claims the bot won both Mario AI competitions in 2009.

                                    You can see the path it plans to go as a red line, which updates when it detects new obstacles at the right screen border. It uses only information visible on screen.”

                        See also http://www.marioai.org/.

 

            Optional Cultural Interest:

                     A* Search in Interplanetary Trajectory Design, courtesy of Eric Trumbauer, former CS-271 student.

                                    Eric comments, “One thing to possibly discuss with the last slide is that the itinerary it settles on does stay at a higher energy for a little bit until it passes closest to Europa, maximizing the velocity before the insertion sequence to the lower energy.  This is indeed optimal behavior, as opposed to immediately reducing its energy as a Greedy Best First algorithm using this heuristic would want to do.”

                        A* Search in Protein Structure Prediction, Lathrop and Smith, J. Mol. Biol. 255(1996)641-665

 

            Optional Cultural Interest:

                        Singularity Institute for Artificial Intelligence- P1/2 - Video Dailymotion

                        Singularity Institute for Artificial Intelligence

                        Singularity Institute - Wikipedia, the free encyclopedia

                        Singularity Institute home page

                       

            Tue., 8 Oct., Local Search.

Read in advance:  Textbook Chapter 4.1-4.2.

                        Lecture slides (two parts):

                                    (1) Local Search [PDF; PPT]; and

                                    (2) Representation [PDF; PPT].

 

Optional URL:

            Boxcar 2D

                                    The program learns to build a car using a genetic algorithm

            Optional Reading:
                        Minton, et. al., 1990, AAAI "Classic Paper" Award recipient in 2008.

                                    How to solve the 1 Million Queens problem and schedule space telescopes.

            Optional Lecture Slides:

                        Review Search [PDF; PPT].

            Optional Ungraded Homework:

                        Homework #1; answer key.

Week 3:

            Thu., 10 Oct., Quiz #1 (answer key here); start Constraint Satisfaction.

Read in advance: Textbook Chapter 6.1-6.4, except 6.3.3.

                        Lecture slides: Constraint Satisfaction Problems [PDF; PPT].

 

            Optional Cultural Interest:

                        Google Goggles

            Optional Reading:

                        Campbell, et al., 2002, Artificial Intelligence, “Deep Blue.” [PDF]

                                    (URL http://www.sciencedirect.com/science/article/pii/S0004370201001291)

 

            Tue., 15 Oct., finish Constraint Satisfaction.

                        Read in advance: Textbook Chapter 6.1-6.4, except 6.3.3.

                        Lecture slides: Constraint Satisfaction Problems (above).

 

Optional Cultural Interest:

                        Arthur C. Clarke “Quarantine.”

                                    A science fiction short story written by a classic master, in 188 words.

                                    He was challenged to write a science fiction short story that would fit on a postcard.

Optional Reading: Chaslot, et al., “Monte-Carlo Tree Search: A New Framework for Game AI,”

in Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference,

AAAI Press, Menlo Park, pp. 216-217, 2008.

            An interesting combination of Local Search (Chapter 4) and Game Search (Chapter 5).

Optional URL: “Everything Monte Carlo Tree Search” website.

            Optional Ungraded Homework:

                        Homework #2; answer key.

Week 4:

            Thu., 17 Oct., Extra lecture on Constraint Satisfaction in support of your coding project.

            Tue., 22 Oct., start Games/Adversarial Search.

Read in advance: Textbook Chapter 5.1-5.5.

                        Lecture slides: Games/Adversarial Search [PDF; PPT].

 

            Optional Cultural Interest:

                        Google Car: It Drives Itself - ABC News

                        [Part 1/3] The Evolution of Self-Driving Vehicles

                        [Part 2/3] How Google's Self-Driving Car Works                  

                        [Part 3/3] Google's Self-Driving Golf Carts

                        DARPA Urban Challenge Highlights

                        Princeton DARPA Grand Challenge - Crash Video

                        DARPA Urban Challenge: Ga Tech hits curb

                        DARPA Urban Challenge - Sting Racing crash

                        [DARPA] Team Oshkosh attempts forced Entry to Main Exchange

                        [DARPA] Alice's Crash (spectator view)

                        [DARPA] Alice's Crash (road-finding camera) [different view of above; long]

                        DARPA Urban Challenge Crash Cornell MIT

                        DARPA Urban Challenge - robot car wreck [different view of above]

            Optional Reading:

                        Autonomous car - Wikipedia, the free encyclopedia

                        Autonomous Driving in Traffic: Boss and the Urban Challenge” (2009).

                        Stanley: The Robot that Won the DARPA Grand Challenge” (2005).

Week 5:

            Thu., 24 Oct., finish Games/Adversarial Search.

Read in advance: Textbook Chapter 5.1-5.5.

            Lecture slides: Games/Adversarial Search (above).

 

            Optional Cultural Interest:

                        Quadrocopter Pole Acrobatic

                        Nano Quadcopter Robots swarm video

                                    The Stanford Autonomous Helicopter performing an aerobatic airshow under computer control:

                        “Stanford Autonomous Helicopter - Airshow #1”

                        “Stanford Autonomous Helicopter - Airshow #2 Redux

            Optional Cultural Interest:

                        RoboCup 2012 Standard Platform: USA / Germany (Final).

            Optional Ungraded Homework:

                        Homework #3; answer key.

 

            Tue., 29 Oct., Quiz #2 (answer key here); start Propositional Logic.

                        Read in advance: Textbook Chapter 7.1-7.4.

                        Lecture slides: Propositional Logic A [PDF; PPT].

 

            Optional Cultural Interest:

                        High-Speed Robot Hand

                        “Janken (rock-paper-scissors) Robot with 100% winning rate”

                        CubeStormer II”

 

Week 6:

 

            Thu., 31 Oct., finish Propositional Logic.  HAPPY HALLOWEEN!!

                        Read in advance: Textbook Chapter 7.5 (optional: 7.6-7.8).

                        Lecture slides: Propositional Logic B [PDF; PPT].

                                    Additional Discussion lecture slides [PDF].

 

            Optional Halloween URLs (snakes, spiders, and a talking head!):

                        Snake Robot Climbs a Tree

                        Asterisk - Omni-directional Insect Robot Picks Up Prey #DigInfo

                        Freaky AI robot, taken from Nova science now

            Optional Reading:

Alan Turing’s classic paper on AI (1950).

            Alan Turing is the most famous computer scientist of all time.

The Turing Award is the highest honor in computer science.

The Turing Machine is still our fundamental theoretical model of computation.

Turing’s work on the Enigma code in WWII led to programmable computers.

            AAAI/AI Topics: The Turing Test: “Can Machines Think?”

            Wikipedia “Computing Machinery and Intelligence

            No homework --- study for the Mid-term Exam.

 

            Tue., 5 Nov., Catch-up, Review for Mid-term Exam.

Read in advance: Textbook Chapters 1-7 (only sections assigned above).

                        Lecture slides: Catch-up, Review, Question&Answer [PDF; PPT].

Week 7:

            Thu., 7 Nov., Mid-term Exam (answer key here).

Read in advance: Textbook Chapters 1-7 (only sections assigned above).

                        Lecture slides: Catch-up, Review, Question&Answer (above).

 

            Optional Ungraded Homework:

                        Homework #4; answer key.

 

            Tue., 12 Nov., Review Mid-term Exam; start First Order Logic

Read in advance: Textbook Chapter 8.1-8.2.

                        Lecture slides: First Order Logic Syntax [PDF; PPT].

 

            Optional Cultural Interest:

                        Singularity Institute for Artificial Intelligence- P1/2 - Video Dailymotion

                        Singularity Institute for Artificial Intelligence

                        Singularity Institute - Wikipedia, the free encyclopedia

                        Singularity Institute home page

Week 8:

            Thu., 14 Nov., finish First Order Logic; Knowledge Representation.

Read in advance: Textbook Chapter 8.3-8.5.

                        Lecture slides (two parts):

(1) First Order Logic Semantics [PDF; PPT]; and

(2) First Order Logic Knowledge Representation [PDF; PPT].

 

            Optional Lecture slides: First Order Logic Inference [PDF; PPT].

Read in advance: Textbook Chapter 9.1-9.2, 9.5.1-9.5.5.

            Optional Reading:

Ferrucci, et al., 2010, “Building Watson: An Overview of the DeepQA Project

            Optional Ungraded Homework:

                        Homework #5; answer key.

 

            Tue., 19 Nov., Quiz #3 (answer key here); Probability, Uncertainty, Bayesian Networks.

            Lecture by Will Devanny, CS-171 TA.

Read in advance: Textbook Chapters 13, 14.1-14.2.

(Please note: Will Devanny is revising the lecture slides, check back later for current version.)

                        Lecture slides: Reasoning Under Uncertainty [PDF; PPT].

 

            Optional Cultural Interest:

                        Video of Judea Pearl’s 2011 Turing Award lecture.

                        The Mechanization of Causal Inference: A “mini” Turing Test and Beyond.

            Optional URL: “Peter Norvig 12. Tools of AI: from logic to probability.

Week 9:

            Thu., 21 Nov., start Learning from Examples.

Read in advance: Textbook Chapter 18.1-18.4.

                        Lecture slides: Intro to Machine Learning [PDF; PPT].

 

            Optional Cultural Interest:

                        IBM simulates 530 billon neurons, 100 trillion synapses on supercomputer

                        Speech Recognition Breakthrough for the Spoken, Translated Word

            Optional Reading:

                        Cyc is a large-scale knowledge-engineering project:

                                    Searching for Commonsense: Populating Cyc from the Web, Matuszek et al, AAAI 2005

                                    Additional background.

                                    Cyc home page.

                                    Additional Cyc publications.

                                    Cyc - Wikipedia, the free encyclopedia.

            Optional Ungraded Homework:

                        Homework #6; answer key.

 

            Tue., 26 Nov., finish Learning from Examples.

Read in advance: Textbook Chapter 18.5-18.12, 20.1-20.3.2.

                        Lecture slides:

                                    Learning Classifiers [PDF; PPT].

 

            Optional Lecture slides: Viola & Jones, Learning, Boosting, Vision [PDF; PPT] (read the two papers immediately below)

                        Optional Reading: Viola & Jones, 2004, “Robust Real-Time Face Detection

                        Optional Reading: Freund & Schapire, 1999, “A Short Introduction to Boosting

            Optional Reading: Danziger, et al., 2009, “Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active Learning

Week 10:

            Thu., 28 Nov., Thanksgiving Day Holiday

           

            Tue., 3 Dec., Special Topics, TBD.  Probably Clustering (= unsupervised learning and prediction) and Regression (= statistical numeric learning and prediction).

Reading: Textbook Chapter 18.6.1-2, 20.3.1.

                        Lecture slides:

                                    Clustering (Unsupervised Learning) [PDF; PPT].

                                    Linear Regression [PDF; PPT].

 

                        Optional link: Fast Robots

Week 11:

            Thu., 5 Dec., Quiz #4 (answer key here); Catch-up, Review for Final Exam.

Read in advance: Textbook, review all assigned reading.

                        Lecture slides: Review, Catch-up, Question&Answer [PDF; PPT].

 

Project due date:

            Fri., 6 Dec., Project due (Friday midnight): Monster Sudoku

 

Final Exam:

Thu., 12 Dec, 1:30-3:30pm Final Exam (answer key here).

Project:

The coding project this term will be “Monster Sudoku Solver.” Standard Sudoku is played on a 9x9 grid subdivided into nine 3x3 boxes. Every row, column, and box must contain the digits 1 through 9 exactly once. Monster (or Mega) Sudoku is similar, but the grid and boxes are bigger. 12x12 puzzles are played with the numbers 1 to 9 and A, B and C in each row, column, and 3x4 box. 16x16 puzzles are played with 1 to 9 and the letters A to G in each row, column, and 4x4 box.

An Introduction is available here.  A Specification is available here.

The specification has been revised to contain an Appendix that gives pseudo-code for converting between odometer strings and unsigned fixnums.  For your convenience in testing and debugging, the first 44135 odometer values (“1” to “ZZZ”) and their unsigned fixnum equivalents (0 to 44134) are available here. Because I enjoy coding, I have coded the conversion routines in my favorite language, Lisp (available here).

See for example:

http://www.dailysudoku.com/sudoku/archive.shtml?type=monster

http://www.universaluclick.com/games/sudokumonster

http://www.knightfeatures.com/KFWeb/content/features/kffeatures/puzzlesandcrosswords/KF/Sudoku/Sudoku_Monster/sudoku_monster.html

http://www.conceptispuzzles.com/index.aspx?uri=puzzle/sudoku/mega

 

A previous offering of CS-171 coded a Sudoku solver using the Constraint Satisfaction Problem (CSP) methods we will study, but the methods proved to be too powerful for Sudoku and even the basic methods could solve hard Sudoku puzzles easily.  I hope Monster Sudoku will provide more of a challenge.

 

The project description for the old Sudoku Solver is available here.

 

Several of my various CS-171 projects 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 interesting AI project shells.  Please let me know if this is of interest to you (CS-171 grade of A- or better required).

Study Guides --- Previous CS-171 Quizzes, Mid-term, and Final exams:

Previous CS-171 Quizzes, Mid-term exams, and Final exams are available here as study guides.

 

As an incentive to study this material, at least one question from a previous Quiz or Exam will appear on every new Quiz or Exam. In particular, questions that many students missed are likely to appear again. If you missed a question, please study it carefully and learn from your mistake --- so that if it appears again, you will understand it perfectly.

 

Fall Quarter 2013:

Quiz #1 and key

Quiz #2 and key

Quiz #3 and key

Quiz #4 and key

Mid-term Exam and key

Final Exam and key

 

Fall Quarter 2012:

Quiz #1 and key

Quiz #2 and key

Quiz #3 and key

Quiz #4 and key

Mid-term Exam and key

Final Exam and key

 

Winter Quarter 2012:

Quiz #1 and key

Quiz #2 and key

Quiz #3 and key

Quiz #4 and key

Mid-term Exam and key

Final Exam and key

 

Spring Quarter 2011:

Quiz #1 and key

Quiz #2 and key

Quiz #3 and key

Quiz #4 and key

Quiz #5 and key

Mid-term Exam and key

Final Exam and key

 

Spring Quarter 2004:

Quiz #1 key

Quiz #2 key

Quiz #3 key

Quiz #4 key

Quiz #5 key

Quiz #6 key

 

Spring Quarter 2000:

Quiz #1 key

Quiz #2 key

Quiz #3 key

Quiz #4 key

Quiz #5 key

Final Exam key

Online Resources:

Additional Online Resources may be posted as the class progresses.

Textbook website for Artificial Intelligence: A Modern Approach (AIMA).

            AIMA page for additional online resources.

Website for American Association for Artificial Intelligence (AAAI).

            (apparently some of below has gone away in recent AAAI website reorganization?)

            AAAI “AI Topics.”

            AAAI “Student Resources.”

            AAAI “Classic Papers.”

            AAAI Annual Conference.

 


 

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 Senate Academic Honesty Policies 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. Dr. Lathrop seeks to create a level playing field for all students.