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CS156 Fall 2022 Sec5 Home Page/Syllabus

Introduction to Artificial Intelligence

Instructor: Chris Pollett
Office: MH 214
Phone Number: (408) 924 5145
Office Hours: MW 12:15-1:15pm
Class Meets:
Sec5 MW 1:30-2:45pm in MH223


To take this class you must have taken:
with a grade of C- or better.

Texts and Links

Required Texts: Artificial Intelligence: A Modern Approach. 4th Ed.. Stuart Russell and Peter Norvig
Online References and Other Links: Official Python Website.
Python Implementation of code from book.


From the catalog: Basic concepts and techniques of artificial intelligence: problem solving, search, deduction, intelligent agents, knowledge representation. Topics chosen from logic programming, game playing, planning, machine learning, natural language, neural nets, robotics. My abstract: Algorithms which allow computers to simulate various abilities of living organisms are used in many different areas of computer science. In computer gaming it is important to be able to be able to create agents which behave intelligently in response to human players. In search engines it is important to be able to classify the types of queries which are arriving to better tailor search results. Question answering systems used in medicine have recently attracted attention after the defeat of the top Jeopardy champions by Watson, a computer program from IBM. Self-driving cars need to be able to plan, detect, and classify objects in their environment. This course will survey the major areas of AI. The course will begin with problem solving algorithms. In particular, search space exploration strategies such as iterative deepening, A*, and several local search algorithms will be considered. Techniques to solve constraint satisfaction problems will then be discussed. This will be followed by a description of the minimax algorithm and alpha-beta pruning which is used in games such as chess. The focus will then shift to representation schemes for knowledge, logical reasoning and theorem proving techniques. Then task planning algorithms will be considered. Finally, the semester will conclude with an introduction to neural nets, learning algorithms, and AI related to information retrieval.

Course Learning Outcomes (CLOs)

By the end of this course, a student should be able to:

CLO1 -- Find solution nodes in a state space using the A* algorithm.

CLO2 -- Explain the advantages and disadvantages of the following techniques: (a) breadth-first search compared to depth-first search, (b) informed search compared to uninformed search, hill climbing, STRIPS/PDDL representations for planning.

CLO3 -- Apply forward checking in constraint satisfaction problems.

CLO4 -- Apply alpha-beta pruning in adversarial search.

CLO5 -- Translate sentences in first-order logic to conjunctive normal form (CNF).

CLO6 -- Find proofs by using resolution.

CLO7 -- Implement at least one machine learning algorithm.

CLO8 -- Students should be able to describe: (a) the frame problem, (b) Possible representations for time and for beliefs.

Course Schedule

Below is a tentative time table for when we'll do things this quarter:

Week 1:Aug 22, Aug 24 Ch 1-2 (Intro to AI, Intelligent Agents) from Russell and Norvig
Week 2:Aug 29, Aug 31 Start Ch 3 (Search) A* Algorithm, Python
Week 3:Sep 5 (Labor Day), Sep 7 More Python
Week 4:Sep 12, Sep 14 Finish Ch 3, Start Ch 4 Local Search
Week 5:Sep 19, Sep 21 Finish Ch 4, Start Ch 5 Adversarial Games
Week 6:Sep 26, Sep 28 Finish Ch 5, Start Ch 6 Constraint Satisfaction Problems
Week 7:Oct 3, Oct 5 Finish Ch 6, Ch 7 Start Logical Agents
Week 8:Oct 10, Oct 12(Midterm) Review
Week 9:Oct 17, Oct 19 Ch 8 First-Order Logic
Week 10:Oct 24, Oct 26 Ch 9 Inference in First-Order Logic
Week 11:Oct 31, Nov 1 Ch 11 Automated Planning
Week 12:Nov 7, Nov 9 Ch 10 Knowledge Representation, Start Ch 12 Quantifying Uncertainty
Week 13:Nov 14, Nov 16 Ch 13 Probabilistic Reasoning (Bayesian Networks)
Week 14:Nov 21, Nov 23 (No Class) Ch 19 Learning with Examples
Week 15:Nov 28, Nov 30 Ch 20 Learning with Probabilistic Models
Week 16:Dec 5(Hw5) Review
The final will be Tuesday, Dec 13 from 12:15-2:30 PM


HWs and Quizzes 50%
Midterm 20%
Final 30%

Grades will be calculated in the following manner: The person or persons with the highest aggregate score will receive an A+. A score of 55 will be the cut-off for a C-. The region between this high and low score will be divided into 8 equal-sized regions. From the top region to the low region, a score falling within a region receives the grade: A, A-, B+, B, B-, C+, C, C-. If the boundary between an A and an A- is 85, then the score 85 counts as an A-. Scores below 55 but above 50 receive the grade D. Those below 50 receive the grade F.

If you do better than an A- in this class and want me to write you a letter of recommendation, I will generally be willing provided you ask me within two years of taking my course. Be advised that I write better letters if I know you to some degree.

Course Requirements, Homework, Quiz Info, and In-class exercises

This semester we will have five homeworks, weekly quizzes, and weekly in-class exercises.

Every Monday this semester, except the first day of class, the Midterm Review Day, and holidays, there will be a quiz on the previous week's material. The answer to the quiz will either be multiple choice, true-false, or a simple numeric answer that does not require a calculator. Each quiz is worth a maximum of 1pt with no partial credit being given. Out of the total of twelve quizzes this semester, I will keep your ten best scores.

On Wednesday's, we will spend 15-20 minutes of class on an in-class exercise. You will be asked to post your solution to these exercises to the class discussion board. Doing so is worth 1 "insurance point" towards your grade. A "insurance point" can be used to get one missed point back on a midterm or final, up to half of that test's total score. For example, if you scored 0 on the midterm and have 10 insurance points, you can use your insurance points, so that your midterm score is a 10. On the other hand, if you score 18/20 on the midterm, you can use at most 1 insurance point since half of what you missed (2pts) on the midterm is 1pt.

Links to the current list of homeworks and quizzes can be found on the left hand side of the class homepage. After an assignment has been returned, a link to its solution (based on the best student solutions) will be placed off the assignment page. Material from assignments may appear on midterms and finals. For homeworks you are encouraged to work in groups of up to three people. Only one person out of this group needs to submit the homework assignment; however, the members of the group need to be clearly identified in all submitted files.

Homeworks for this class will be submitted and returned completely electronically. To submit an assignment click on the submit homework link for your section on the left hand side of the homepage and filling out the on-line form. Hardcopies or e-mail versions of your assignments will be rejected and not receive credit. Homeworks will always be due by midnight according to the departmental web server on the day their due. Late homeworks will not be accepted and missed quizzes cannot be made up; however, your lowest score amongst the five homeworks and your quiz total will be dropped.

When doing the programming part of an assignment please make sure to adhere to the specification given as closely as possible. Names of files should be as given, etc. Failure to follow the specification may result in your homework not being graded and you receiving a zero for your work.

Classroom Protocol

I will start lecturing close to the official start time for this class modulo getting tangled up in any audio/visual presentation tools I am using. Once I start lecturing, please refrain from talking to each other, answering your cell phone, etc. If something I am talking about is unclear to you, feel free to ask a question about it. Typically, on practice tests days, you will get to work in groups, and in so doing, turn your desks facing each other, etc. Please return your desks back to the way they were at the end of class. This class has an online class discussion board which can be used to post questions relating to the homework and tests. Please keep discussions on this board civil. This board will be moderated. Class and discussion board participation, although not a component of your grade, will be considered if you ask me to write you a letter of recommendation.


The midterm will be during class time on: Oct 12.

The final will be: Tuesday, Dec 13 from 12:15-2:30 PM.

All exams are closed book, closed notes and in this classroom. You will be allowed only the test and your pen or pencil on your desk during these exams. The final will cover material from the whole semester although there will be an emphasis on material after the last midterm. No make ups will be given. The final exam may be scaled to replace a midterm grade if it was missed under provably legitimate circumstances. These exams will test whether or not you have mastered the material both presented in class or assigned as homework during the quarter. My exams usually consist of a series of essay style questions. I try to avoid making tricky problems. The week before each exam I will give out a list of problems representative of the level of difficulty of problems the student will be expected to answer on the exam. Any disputes concerning grades on exams should be directed to me, Professor Pollett.


If you believe an error was made in the grading of your program or exam, you may request in person a regrade from me, Professor Pollett, during my office hours. I do not accept e-mail requests for regrades. A request for a regrade must be made no more than a week after the homework or a midterm is returned. If you cannot find me before the end of the semester and you would like to request a regrade of your final, you may see me in person at the start of the immediately following semester.

University Policies and Procedures

Students registered for a College of Science (CoS) class with an in-person component should view the CoS COVID-19 and Monkeypox Training slides for updated CoS, SJSU, county, state and federal information and guidelines, and more information can be found on the SJSU Health Advisories website. By working together to follow these safety practices, we can keep our college safer. Failure to follow safety practice(s) outlined in the training, the SJSU Health Advisories website, or instructions from instructors, TAs or CoS Safety Staff may result in dismissal from CoS buildings, facilities or field sites. Updates will be implemented as changes occur (and posted to the same links).

Per University Policy S16-9, university-wide policy information relevant to all courses, such as academic integrity, accommodations, etc. will be available on Office of Graduate and Undergraduate Programs' Syllabus Information web page at Below are some brief comments on some of these policies as they pertain to this class.

Academic Integrity

For this class, you should obviously not cheat on tests. For homeworks, you should not discuss or share code or problem solutions between groups! At a minimum a 0 on the assignment or test will be given. A student caught using resources like Rent-a-coder will receive an F for the course. Faculty members are required to report all infractions to the Office of Student Conduct and Ethical Development.


If you need a classroom accommodation for this class, and have registered with the Accessible Education Center, please come see me earlier rather than later in the semester to give me a heads up on how to be of assistance.