This is the main web page for Section 103 of the course CS 370, Introduction to Artificial Intelligence taught in the fall semester of 2022 at NJIT.
This page will be updated throughout the semester. Students are expected to visit this page periodically.
NEW SLACK INVITE: https://join.slack.com/t/cs370introaifall2022/shared_invite/zt-1isjvxowj-5wLPmO2NYrzO46_Yq71teQ
(expires Nov 28 --- ask instructor for a new one after this date)
Contents
- What is the course about?
- When and where are the lectures?
- Who is the instructor?
- Am I qualified to take this course?
- Where is the course schedule/Canvas/homework page?
- Where is the course schedule?
- When and where are the exams?
- What is the main textbook?
- Do I have to attend all the lectures?
- What is expected of an NJIT student?
- Can I use electronic devices during lecture?
- What is the grading policy?
- Where can I find the homework?
- Can I turn in assignments after the deadline?
- Is it possible to make-up a missed exam?
- (How) Should I ask questions?
- Is tutoring available?
- Can I email the instructor?
- What if I have a disability?
Description. "An exploration of concepts, approaches and techniques of artificial intelligence. Emphasizes both underlying theory and applications. Topics include knowledge representation, parsing language, search, logic, adduction, uncertainty, and learning. Some subset of the following programming languages will be used: LISP, Prolog, Python, and Scala. Students are required to do programming assignments, complete a programming term project and review case studies."
Source. NJIT course catalog
Lecture Time and Location. 18:00--20:50 Friday in KUPF 202
Instructor. Dr. William DeMeo
Email. williamdemeo at gmail
Office location. GITC 4201A
Office hours. Wednesdays 14:00--16:00
Students should have achieved a grade of C or better in CS 114 and either MATH 226 or CS 241.
Course Schedule.
The page at github.com/williamdemeo/cs370-fall2022/schedule provides a tentative lecture and homework schedule (subject to change).
Readings refer to the fourth edition of the required textbook (AIMA) unless otherwise indicated.
Canvass page. TBA
Homework page. The homework information page is at github.com/williamdemeo/cs370-fall2022/homework.
The Gradescope page for this class is here.
All exams take place in our usual classroom, KUPF 202.
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MIDTERM EXAM
Topics. Agents and Environments, Uninformed Search, Informed Search, A* Search and Heuristics, CSP I, CSP II, Adversarial Search I, Adversarial Search II, Markov Decision Processes I, Markov Decision Processes II, Reinforcement Learning I, Reinforcement Learning II, Probability, Bayes Nets I
DATE. TBA -
FINAL EXAM (cumulative)
DATE. TBA
TIME. TBA
PLACE. KUPF Rm. 202
In accordance with university policy, the final exam must be taken by all students at the scheduled time in the usual classroom. Do not make plans which would have you depart campus before the scheduled final exam date.
Students are expected to have access to the following textbook:
Artificial Intelligence: A Modern Approach, 4th Edition (AIMA)
ISBN. 9780134610993
Author. Russell
Publisher. Pearson
Year. 2020
These are not required but might be helpful.
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Online courses and videos
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Books
- Reinforcement Learning: an introduction by Sutton and Barto
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Papers
- Distributed Representations of Words and Phrases and their Compositionality by Mikolov, et al. (the Word2vec paper)
- Asynchronous Methods for Deep Reinforcement Learning by Mnih, et al.
- Curiosity-driven Exploration by Self-supervised Prediction by Pathak, et al.
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Miscellaneous
- OpenAI (creators of GPT3)
- The Ghost in the Machine episode of This American Life, in which "people use machines to find people they lost."
- A robot wrote this article. Are you scared yet, human?
Yes. Students are expected to attend all classes. A grade penalty will be exacted if you have an excessive number of absences (whether excused or unexcused). Specifically, you are permitted (but strongly discouraged from taking) five absences in total, and you must email the instructor if/when you miss a class. Each additional absence, and any absence not mentioned to the instructor, may result in the deduction of points from your final grade.
Occasionally attendance will be recorded at the start of class.
Important. If you plan to leave before class is over, the correct procedure is to mention this to the professor before the start of class. It is impolite and disruptive to your classmates to leave, or even pack up your belongings, before the lecture is over.
Students must abide by the university's code of conduct. In particular, cheating is unacceptable and will not be tolerated. Violations of this policy will be dealt with in a manner consistent with university regulations, which range from a warning to expulsion from the university.
No. Use of electronic devices in lecture for purposes unrelated to the course is not allowed.
However, laptops or tablets may be used in the classroom for work related to this course.
As a general rule, students should silence and refrain from using electronic devices, such as phones, ipods, microwave ovens, etc. in class. There is one exception to this rule: a laptop or tablet may be used for working on something related to the course material.
Tiktoking, Tweeting, Tindering, Facebooking, Instagramming, Snapchatting, Whatsapping, YouTubing, and gaming are not allowed. Such activities make it hard, if not impossible, for the student to concentrate on the lecture and can also be very distracting to other students and the instructor. Students who violate this policy may be asked to leave the classroom.
The breakdown of the final course grade is as follows:
- Homework: 30 points total
- Projects: 40 points total
- Midterm exam: 10 points
- Final exam: 20 points
At the end of the semester, letter grades will be assigned roughly according to the following table. However, the scale may be shifted depending on overall student performance.
- A: 91--100
- B+: 86--90
- B: 81--85
- C+: 76--80
- C: 71--75
- D+: 66--70
- D: 60--65
- F: 0--59
All homework will be submitted online on Gradescope. See the tentative course schedule.
The lowest (or missed) homework score will be dropped and not counted toward the final course grade.
Descriptions and pdf versions of each homework assignment will be available in the homework directory of this repository for your reference, but you must complete and submit the homework online on the Gradescope web site for this course.
You are strongly encouraged to start the homework early so that you have time to get help from the instructor or a tutor if you need it.
No late homework will be accepted. However, if many students are struggling to complete a particular homework assignment and if they communicate these difficulties with their instructor before the homework deadline, it is possible that a class-wide extension may be granted. Also, if you fail to submit homework on time, this will not necessarily hurt your final course grade since the lowest homework score will be dropped.
Generally speaking, there are no make-up exams. However, if you must miss an exam for one of the legitimate reasons listed below, and if you contact the professor at least five days before the exam date, then you might be able to take a make-up exam before the scheduled exam time.
To request a make-up exam, a student must provide documented evidence of one of the following:
- Documented medical excuse - student's own medical emergency.
- Documented medical excuse - a member of the student's family has a medical emergency.
- Extra curricular activity sponsored University of Colorado.
- Armed forces deployment (military duty).
- Officially mandated court appearances, including jury duty.
- A conflict with another exam or if you have three or more final exams on a given day. (In each case the exam with the fewest students must arrange the make-up exam.)
If you miss an exam due to some unforeseen circumstance, you must contact the professor within one class meeting after the missed test and provide an explanation. If your excuse is accepted, the missed test score may be replaced with 80% of your final exam score. For example, if your excuse is accepted and you score a 90% on the final, then you will receive a 72% for the missed test (0.80*0.90 = 0.72).
Students are strongly encouraged to ask lots of questions. If you don't understand something, please ask!
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In Lecture. The best time/place to ask a question is during lecture or recitation or office hours.
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On Canvas. Another good place to ask a question is the online discussion forum. The Canvas system is designed to provide help quickly and efficiently. Rather than emailing questions to the teaching staff, students are encouraged to post questions on Canvas.
"YWCC and its ACM student chapter have partnered to create an online tutoring program available to undergraduate and graduate students looking for tutoring assistance."
See computing.njit.edu/tutoring for more information.
The undergraduate tutoring schedule is available at computing.njit.edu/undergraduate-tutoring-1
You may email the instructor directly, though the response time might be a slower than if you use one of the preferred methods described above.
If you email the instructor, please use an informative subject field. Using this link will populate your message fields with some of the required information. If you do not at least indicate which class you are in, your email will be at risk of going unanswered.
If you believe that you have a disability that qualifies under the Americans with Disabilities Act and Section 504 of the Rehabilitation Act and requires accommodations, you should contact the Office of Accessibility Resources and Services for information on appropriate policies and procedures. The next step is to talk to the instructor who will be happy to assist with accommodations, but will not provide them retroactively (so file the appropriate requests and paperwork well before the first exam!).
Students must have their paper work in order and should contact the instructor early in the semester in order to have their learning needs appropriately met.