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 to get programming skills of developing AI applications. 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). 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 remotely in Fall 2021 including 3 (2+1) hours of synchronous lectures per week and 1h of synchronous lab/tutorial per week, for 12 weeks. The lectures will be delivered over Zoom, but they will not be recorded. Students are not allowed to record the lectures. Before joining a lecture, sign in using Single Sign On (SSO), i.e., authenticate with your   my.ryerson.ca   credentials. Ryerson international students enrolled in CPS721 can access Zoom through   global.ryerson.ca - a proxy service similar to a virtual private network (VPN). This service can be accessed only outside of Canada, US and Mexico. The Zoom links and passwords are posted from a CPS721 course shell on my.ryerson.ca accessible to all students enrolled in CPS721. It is required to register for lectures in advance using your Ryerson login.
  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.


• Compulsory 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, 1136p. The students can either buy, or rent. In addition, students can purchase an electronic copy of this book directly: $49.99 (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.

  Common Sense, the Turing Test, and the Quest for Real AI by Hector Levesque. Published by the MIT Press, paperback, $17(US), 192pp, March 2018, ISBN: 9780262535205.

• 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

• Grading requirements: To pass the course you have to get at least 50% of the total course marks calculated from homework assignments, labs, midterm test and the final exam.
  
• 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 over Zoom are copyrighted and protected by law. You cannot share them with anyone. You cannot repost them anywhere on the Web. Please review the Ryerson University 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 Ryerson University Academic Policy 60. You can read parts of this policy online related to "Academic misconduct".
• The policy for remote synchronous content delivery over Zoom: the students are expected to use a Chat Window only for asking or answering lecture-related questions, but not for personal communication. The students are expected to pay attention to a lecture and volunteer to answer instructor's questions during the class-time. The students are normally expected to keep their mics mute and unmute them only to answer instructor's questions. The students can keep their video on (recommended) to facilitate communication. They might be asked to participate in unannounced polls or quizzes. The Ryerson University has issued a minimum technlogy requirement for remote learning. The policy about electronic devices for in-person lecture delivery: 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. Each exam may include two components: written and oral, the latter can be individual. More specifically, selected students can be invited to 1:1 personal meeting with an instructor where they can be asked to solve the problems similar to a written exam. If the student invited to an oral exam fails to attend it, then the exam mark can be reduced to zero. 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 submit an academic consideration request through the Online Submission Form   and   hand in a hard copy of a completed official Health Certificate to the department of Computer Science within 3 working days. You have to bring your documents yourself to the CS front reception desk. Once the Program Department has verified the student’s health documentation, the instructor will be notified of the verification. Similarly, all documentation related to special accomodation or academic consideration should be submitted to the CS program office within the specified time limits.


• Dates are subject to change, all changes will be announced in class and on the course Web pages.
• 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). No late assignments will be accepted in Fall 2021. Start solving your assignment on the same day when it is posted. Do not procrastinate. No make-up assignments.
• All assignments have to be submitted electronically on D2L into the specified folder. The CPS721 students are expected to solve homework assignments in small groups of 2-3 students. These students can be from different sections. However, a group can include only either students from the sections 1,2,3,4 or exclusively students from the sections 5,6,7,8. The students from Sections 1,2,3,4 cannot collaborate with the students from Sections 5,6,7,8. 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, I 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 5% (or less) extra credit may be assigned for active class participation throughout the term, e.g., a student attends most of the classes, participates actively by asking/answering questions, solves exercises in class. Class participation marks are earned for active course participation and given at discretion of the course instructor. The course participation marks cannot be requested by the students.
• Tutorials/Labs are mandatory. Each student must attend only the section where s/he is assigned. No transfers between sections are possible. The students have to register for the labs in advance using their Ryerson login. Usually, each tutorial includes a mini-lecture and a few polls/quizzes. Each student must answer poll questions individually. In addition, the TA who is teaching a lab can provide additional practice questions/quizzes. 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 5% participation marks. Lab Marks: are given for attendance and answering correctly poll 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 in polls, and
  3. the student signed up the Zoom session as required, provided a family name and a student number.
  4. There will be no make-up labs. No video recordings of lab, or 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.ryerson.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 Ryerson's email addresses only: you can use either your departmental account (preferred) or your university account to send email. Email sent from Google, Yahoo, Hotmail and any other external email domains can be filtered out as spam and might not reach me. Email messages will be normally answered within 24 hours; however, messages sent on weekend (starting from Friday evening) will be usually answered on Monday.
• Grades for labs, tests and assignments will be normally posted on my.ryerson.ca 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 my.ryerson.ca 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 will be pursued as "contract cheating".

In regard to any and all assessments in this course, the use of any third party (e.g., family member, freelancer, roommate, 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 Ryerson student, you are responsible for familiarizing yourself with the Student Code of Academic Conduct.

ACADEMIC CONDUCT
The policy for remote synchronous content delivery over Zoom: the students are expected to use a Chat Window only for asking or answering lecture-related questions, but not for personal communication. The students can click on a "Raise a hand" icon in the Participants window in Zoom, if they have a questions, or unmute themselves and ask a question verbally. The students are expected to pay attention to a lecture and volunteer to answer instructor's questions during the class-time. The students are normally expected to keep their mics mute and unmute them only to answer instructor's questions. Make sure there are no background noises and no audio distractions in your environment. 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 or taking screen-shots of Zoom window is strictly prohibited since this violates the copyright and privacy policies. Limit communication in Chat Window only to questions/answers related to a lecture. 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 a question, or you know what the next step should be, or you have a question related to the lecture, click on the "Raise Hand" icon in Participants Window in Zoom. If you are chosen, then unmute your mic and speak. 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 27, Monday	2
Assignment 2	October 11, Monday	2
Assignment 3	October 25, Monday	2
Midterm	Friday, October 29, 4-6pm EST	20
Assignment 4	November 15, Monday	2
Assignment 5	November 29, Monday	2
Tutorials/Labs	As per timetable above, from Mon, Sept 13	20
Final Exam	Saturday, Dec 11, from 13:00-15:00 Toronto EST (online)	50
Total		100

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