Course Outline Draft

Course Description

• Summary of Content: There are cognitive tasks that people can do relatively easy, but that can be difficult to program on a computer. There are other cognitive tasks that can be difficult for people, but that can be easily implemented on a computer. Artificial Intelligence (AI) is the science of discovering the principles how both easy and difficult tasks can be approached, and subsequently developing computer systems that can carry out these tasks.


• Educational Objectives: enable students to learn some of the fundamental topics that underly several areas of modern AI and Computer Science. Basic logic and resolution-style reasoning are briefly introduced and applied to solving problems such as combinatorial puzzles. The computationally challenging problems (e.g., scheduling) that involve constraints are discussed too. Other basic notions from discrete structures are briefly reinforced as well, such as basic modular arithmetic, functions and relations, set cardinality and counting. The course introduces basic deductive databases, and declarative conjunctive queries for information retrieval. In addition, part of the course introduces and reinforces techniques of developing recursive programs over general recursive data structures (e.g., such as lists, trees, but other recursive discrete structures are discussed as well). The course introduces basics of parsing and context-free grammars. Several types of search techniques are introduced (and/or reinforced) including brute-force search, recursive backtracking, heuristics, depth- and breadth-first traversals. The course introduces PROLOG, the programming language based on logic programming. The students get a working knowledge of writing basic PROLOG programs. The course introduces syntax and semantics of natural languages (such as English), syntactic analysis, parsing, and context-free grammars. The final part of the course reinforces conditional probability, Bayes Theorem, independence and introduces reasoning in Bayesian Networks.


• Calendar description: This course provides introduction to several important AI problems and techniques, including knowledge representation and reasoning, constraints satisfaction, search, natural language understanding, planning, uncertainty, belief networks, learning. Lectures: 3 hrs.   Tutorials/Labs (including quizzes): 1 hr. Prerequisites: (CPS 305, MTH210, MTH 304 or CPS 305 and CPS 420).


• Learning Objectives: At the end of the course, a successful student will be able to accomplish the following tasks. Formulate and trace conjunctive-style queries in PROLOG to a set of atomic statements representing a deductive database, i.e., a relational database augmented with general recursive rules for new relations. Compare PROLOG lists and identify when they are similar (match) or not. Write recursive PROLOG programs using recursive data structures such as lists and terms. Solve constraint satisfaction problems (CSP) using two different techniques. Be able to explain which of the programs for solving CSP is more efficient and why. Demonstrate ability to conduct analysis of a given context-free grammar. Parse natural language noun phrases or sentences and identify the sources of syntactic ambiguity in them. Solve planning problems using a simple iterative depth-first planner, including ability to implement preconditions of actions and their successor state axioms that describe how facts change due to actions. Compute probabilities for diagnostic and prediction queries from a given Baysian network.

• Course organization: The course is delivered in person including 3 (2+1) hours of lectures per week and 1h of lab/tutorial per week, for 12 weeks. Students are not allowed to record the lectures. Some of the lectures may include problem solving sessions, where the instructor will solve problems similar to homework assignments and similar to exams. All the presentation slides, except of problem solving sessions, will be posted on D2L to faciliate asynchronous learning. The labs may include tutorials and solving typical problems similar to exams and homework assignments.


• Required Text Book: 
  Thinking as Computation: A First Course, written by Hector Levesque. Published by the MIT Press, paperback, 328 pp, August 2017, ISBN: 9780262534741. ( online content). This textbook is available from Indigo, from Amazon.ca, and from AbeBooks (used or new). The students are expected to read assigned chapters from this book in addition to lectures.
• Recommended Reference Books: 
  Stuart Russell and Peter Norvig   Artificial Intelligence: A Modern Approach, 4th edition, Copyright 2020, Publisher: Pearson, ISBN-13: 9780134671932, 1115p. The students can either buy, or rent. In addition, students can purchase an electronic copy of this book directly: $58 (CAD) for 12-month e-Text access.

  Computational Intelligence: A Logical Approach by David Poole, Alan Mackworth and Randy Goebel, ISBN-13: 9780195102703, Publisher: Oxford University Press, 576 pages, 1998.

• Topics (tentative sequence): This course will provide undergraduate-level introduction to several important AI problems and techniques, including deductive reasoning, writing recursive programs over recursive data structures, finding solutions that satisfy a given set of constraints (e.g., computing a schedule or solving a puzzle), understanding natural language (e.g., parsing noun phrases), problem solving and planning, pruning of search space, Bayesian networks. Each topic takes about 2 weeks. A moderate amount of Prolog programming will be required as part of the course.

Course Policies

• Student Evaluation: See the table below with a brief description and a tentative calendar for all course work. To pass the course the following is required:
  • At least 50% must be achieved on the theoretical component (the weighted total of the midterm test, and final exam marks)
  • At least a 50% grade on the weighted total lab mark
  • At least a 50% grade on the remaining practical component (the weighted total of the homework assignments)
  Note that class and lab attendance is mandatory.
  
• The students are strongly encouraged to take notes in class, and study their notes after class. Learning can be a gradual process that requires time and efforts. The students benefit from attending lectures and labs since some important details will be discussed only there. For this reason, attending lectures and tutorials/labs is mandatory.
• All course materials posted on D2L and presented in class are copyrighted and protected by law. You cannot share them with anyone. You cannot repost them anywhere on the Web. Please review the TMU policy about copyrights. Moreover, you cannot post any of your solutions to the labs or to assignments, since doing this would violate the cps721 policy on collaboration, and the TMU Academic Policy 60. You can read parts of this policy online related to "Academic misconduct".
• The policy for in-person content delivery. The students are expected to pay attention to a lecture and volunteer to answer instructor's questions during the class-time. The students might be asked to participate in unannounced polls or quizzes. Turn off your mobile phones and all other electronic devices in class. You can keep your laptop or tablet open only if you use it to take notes in class.
• Examinations: The quizzes, a midterm exam, and the final exam may include problem solving, short essay questions as well as writing Prolog code. The duration of these examinations may be around 15-20 min, 1h40min, and 2h, respectively. Extra quizzes (or polls) can be given at any time in class without prior warning. The midterm and final exam may include questions similar to homework assignments and lab quizzes. The final exam will be cumulative and will include all the material covered throughout the term. There will be no supplemental examination. Grades are earned for the demonstration of knowledge.
• If you miss a midterm test, or a final exam for medical reasons, you have to read Policy 167 Academic Consideration   and   submit a copy of a completed official Health Certificate to the designated contact person within 3 working days. Once the submitted student’s health documentation has been verified the instructor will be notified of the verification. Similarly, all documentation related to special accomodation or academic consideration   should be submitted online to the designated contact person within the specified time limits.


• Dates are subject to change, all changes will be announced in class and on the course Web pages. Sign up on D2L to receive the course announcements.
• Assignments should be submitted on or before the deadline specified in the assignment (you are encouraged to submit assignments earlier). Your assignment is considered late if any part of the assignment is late (even if it is just 1 minute late). The penalty for a late assignment is 10% off. No assignments will be accepted if more than 24 hours late. . Start solving your assignment on the same day when it is posted. Do not procrastinate. No make-up assignments.
• All assignments must be submitted electronically on D2L into the specified folder. The CPS721 students can be possibly asked to solve homework assignments in small groups of 2-3 students. These students can be from any sections. To enroll in a group on D2L, sign up to any group you like. You can switch between groups anytime, and solve different assignments with different partners. The CPS721 students can expect that exam questions will be similar to questions from the homework assignments, or they will include parts of the problems from homework.
• From time to time, we will hand out exercises. The students are expected to solve the exercises, but they will not be graded. However, working on exercises will improve your understanding of this course (and will help you to get better marks on tests).
• Up to 4% (or less) extra credit may be assigned for active class participation throughout the term, e.g., a student participates actively by asking/answering questions in class, and so on. Class participation marks are earned for active course participation, not only for attendance, and given at discretion of the course instructor. The course participation marks cannot be requested by the students. Bonus marks are only eligible for students who got a total of at least 60% on all other class assessments.
• Tutorials/Labs are mandatory. Each student must attend only the section where s/he is assigned. No transfers between sections are possible. Usually, each tutorial includes a mini-lecture and a quiz. All students must form a small lab group of 2-3 people and submit 1 solution to the quiz from their group by the end of the lab. Note the students cannot work alone. The lab group can include only the students from the same section. The students who actively participate in labs and volunteer during the lab to answer the questions of their T.A. may become eligible for extra participation marks. Lab Marks: are given for attendance and solving correctly quiz questions, as specified by T.A. The lab mark will be given only if
  1. the student attends the entire lab in the section where s/he is enrolled,
  2. the T.A. observed the student actively participating in discussion, solving questions from the quiz, and
  3. the student signed up their solution to the quiz as required, provided a family name and a student number. Make sure the family name and student# are clearly readable.
  4. The lab group submitted their solution to the quiz by the end of the lab. Note that late solutions will not be accepted.
  5. There will be no make-up labs and no make-up quizzes. No notes from the labs will be posted. The student who missed a lab should try to solve independently the exercises given during the lab time and verify the solutions with the T.A., or with peers in class.
• Handouts and assignments will be made available on the Web only. More specifically, they will be linked from the cps721 online course shell on my.torontomu.ca Also, you are responsible for visiting the Homework Assignments Web pages regularly and reading all information that is provided or linked from these Web pages. In particular, Frequently Answered Questions (FAQs) related to cps721 home work will be linked from this Web page. These FAQs are considered to be an integral part of the assignment. Before sending your questions by e-mail to the instructor, check these Web pages and a CPS721 course shell on D2L whether similar questions have been already answered. Repeated questions will not be answered.
• Email communication: you can send email from local TMU's email addresses only: you can use either your departmental account (preferred) or your university account to send email. Email sent from Google, Bell, Rogers and any other external email domains can be filtered out as spam and might not reach the instructors. Email messages will be normally answered within 24 hours. However, messages sent on weekend (starting from Friday afternoon) will be usually answered on Monday.
• Grades for labs, tests and assignments will be normally posted on D2L Web site no later than two weeks after the due date (exam date). Marking guides, the assignments and some other course related documents will be posted on D2L only. Feedback will be usually provided to students within two weeks. The students can contact the TA who was responsible for marking, if they have questions about marking, or attend the office hour. Make sure you contact the right person. Missing marks for labs cannot be requested since only those students who attended a lab and actively participated are eligible to get a mark (see the policy for labs above).

Contract Cheating Statement
In regard to any and all assessments in this course, the use of Chegg, or any other similar help site/service/tool will be pursued as "contract cheating".

The use of ChatGPT, CoPilot, Gemini and similar generative Large Language Models (LLM) with the purposes of solving homework problems will be pursued as "a breach of Policy 60: Academic Integrity", if the student accessed them before submitting course work and assessment is presented as if it is one’s own original work without appropriate referencing. Generative LLM tools may only be used for comparison with your own course work that you have already submitted, but not for the creation of submitted work.

In regard to any and all assessments in this course, the use of any third party (e.g., family member, freelancer, room-mate, friend, tutor) to complete work on your behalf will be pursued as "contract cheating" under Policy 60 "Academic Integrity".

Policy 60 Penalty Guidelines for contract cheating (e.g., viewing a solution on Chegg or Discord) that only impacts you: F in course.

Policy 60 Penalty Guidelines for contract cheating that facilitates cheating for others (e.g., posting a question to Chegg): Disciplinary Suspension.

ACADEMIC MISCONDUCT
Committing academic misconduct, such as plagiarism and cheating, will trigger academic penalties including failing grades, suspension and possibly expulsion from the University. As a TMU student, you are responsible for familiarizing yourself with the Student Code of Academic Conduct.

ACADEMIC CONDUCT
The students are expected to pay attention to a lecture and volunteer to answer instructor's questions during the class-time. In the case of in-person classes, in order to create an environment conducive to learning and respectful of others rights, phones and pagers must be silenced during lectures, labs and evaluations. Students should refrain from disrupting the lectures and labs by arriving late and/or leaving before the lecture is finished.

Policy on Non-Academic Conduct
No disruption of instructional activities is allowed. In particular, taking video/photos in class is strictly prohibited since this violates the copyright and privacy policies. Do not send any private messages to other students. Do not distract your peers from learning in class with messages unrelated to lecture. If you know how to answer your instructor's a question, or you know what the next step in a solution should be, or you have a question related to the lecture, then Raise your Hand. Among many other infractions, the Code specifically refers to the following as a violation: ``Disruption of Learning and Teaching - Students shall not behave in disruptive ways that obstruct the learning and teaching environment." In particular, the students can use their electronic devices in class only for taking notes. In difficult cases, penalties can be imposed by the Student Conduct Officer.

Remarking / Recalculation Policy

1. Grades are earned for the demonstration of knowledge.
2. If the assignment/test was manually marked, then read carefully the marking guide for the assignment or test you'd like to be remarked. Your grade may go up, down, or remain the same. The students cannot request remarking of a quiz or any other evaluations that was automatically marked.
3. Remarking request can be only submitted within 10 days of the date when the assignment/test marks were posted. It is your responsibility to check your CPS721 marks as soon as possible. Late regrading and recalculation requests will not be accepted. Also, if a student failed to attend a lab or sign up a quiz, the missing marks for quizzes cannot be requested. There are no make-up quizzes in cps721.
4. Mark can decrease if TA finds something that was incorrectly awarded too high a mark.

Tentative Course Calendar (all changes of dates will be announced)

Course Work	Due Date	Grade Value (%)
Assignment  1	September 24, Tuesday	4
Assignment 2	October 8, Tuesday	4
Assignment 3	October 22, Tuesday	4
Midterm	Friday, October 25, 1h40min (100min), from 6pm in DCC (288 Church St)	20
Assignment 4	November 12, Tuesday	4
Assignment 5	November 26, Tuesday	4
10 Tutorials/Labs	As per timetable above, starting from Monday, September 9, 2024	20
Final Exam	TBA	40
Total		100

The total mark is calculated from the marks for assignments, quizzes, midterm and the final exam.