Meeting time and place: Lecture (001): 4:00 P.M. - 5:15 P.M. Tuesday/Thursday Smith Hall 231.

Instructor:

TAs: The TAs are primarily in charge of grading and office hours. Their names, contact information, and office hours are posted in the "Office Hours" page on the class homepage.

Text: Russel and Norvig, Artificial Intelligence A Modern Approach Pearson, 4rd edition. (Older editions should be sufficient as well.) There may also be other resources linked to the class web page.

COVID-19, Face-Coverings, Symptoms, and Vaccination: The University of Minnesota currently requires all students, staff, and faculty to wear masks when indoors regardless of vaccination status. On August 24, 2021, the University launched a vaccine attestation process for faculty and staff, and on August 27, 2021, launched a vaccine requirement process for students - see the Get the Vax 2.0 initiative. Please stay at home if you experience symptoms of COVID-19 or have a positive COVID-19 test result and consult with your healthcare provider about an appropriate course of action. For COVID-19 excused absences, I will work with you to find the best course of action for missed work and/or class experiences. Please see bottom for additional details.

Class Website: There are a few websites associated with this course: a public cse website, Canvas and gradescope. Canvas will primarily be used for announcements and weight grades. The public cse webpage will have the schedule and any resources used in lecture. Please check the schedule frequently for any changes due to the pacing of the class. Important announcements will also be sent out through email (Labeled with "[CSci4511]" in the title).
Gradescope will be used for homework submission and grading. Gradescope for submiting homework (do not create an account here, I will send out emails with more details)

Prerequisites: Before taking this course, you should have:

• Basic knowledge of computer programming.
• Knowledge of common data structures (graphs and trees).
• Some knowledge of formal logic (propositional and predicate logic).

General Course Description: This course covers the fundamentals of Artificial Intelligence (AI). We will cover: a brief overview, agent definition search (search space, uninformed and informed search, game playing, constraint satisfaction), planning, knowledge representation (logical encodings of domain knowledge, ontologies). Lisp will be used to a small extent and resources are posted on the website. This course will prepare you for more advanced AI topics, such as learning and more advanced modeling.

Writing Intensive Course: As this is a writing intensive course, you will learn how to write technically and succinctly. Feedback will be given on your writings and you will be allowed to resubmit them to improve your score (within two weeks of being returned).

Grading:

For all graded work, please address any concerns within two weeks of receiving the grade. We will not change grades after two weeks. Here is the amount each of the items will contribute to your overall grade:

Homework                                         30%
Writing assignments                              20%
Project                                          15%
Midterm 1 (Tuesday, Oct. 13)                     10%
Midterm 2 (Tuesday, Nov. 16)                     10%
Final Exam (Thursday, Dec. 16)      		 15%

Course Content and Components:

• Readings/Lecture: Approximately 30 pages from the textbook or other papers.
• Homework: There will be 6 homework assignments (5% of the grade each). These are individual assignments and your work submitted must be your own. These may include some (Lisp or python) programming. Late submissions are reduced by 15% for every day late (no credit after a five days). Solution keys will be provided a week after the due date.
• Writing Assignments: There will be 5 homework assignments (4% of the grade each). The first few will be individual like the homework, but later writing assignments will be related to the project and can be done in project groups. Late submissions are reduced by 15% for every day late (no credit after a five days).
• Project: One 50 hour per person project. I encourage you to pick a topic that is personally interesting to you. Artificial intelligence is a broad field and you can frame the topic of your choice in this way.
• Examinations: There will be two midterm exams (10% of the grade each), and a final exam (15% of the grade). Dates for these are listed on the schedule. Exams are open book and notes.

Grading for this course is on an absolute scale, so that the performance of others in the class will not negatively affect your grade. Final grades will be assigned based the following scale:

      93.0% -- 100.0%   A
      90.0% --  93.0%   A-
      87.0% --  90.0%   B+
      83.0% --  87.0%   B
      80.0% --  83.0%   B-
      77.0% --  80.0%   C+
      73.0% --  77.0%   C
      70.0% --  73.0%   C-
      67.0% --  70.0%   D+
      60.0% --  67.0%   D
       0%   --  60.0%   F

Scholastic conduct: Both homework and written assignments are individual assesments (unless explicitly stated otherwise). This means your discussions about the questions can only cover the general approaches necessary to solve the problem. You should never share your work or see another student's answer to any part of the problem. It is also not allowed to work so closely together that your answers appear very similar, even if nothing was ever explicitly shared. If you have any questions about what is and is not allowable in this class, please ask the course instructor.

Disability Accommodations: We desire to make learning rewarding and fun for all students and make every attempt to accommodate anyone who has a desire to learn. If you require special classroom or test-taking accommodations, you need to contact the University Disability Services and also notify the instructor as soon as possible at the start of the semester (no later than 3 weeks prior to the first examination).

COVID-19 Additional Information: People who are not vaccinated are at high risk for getting and spreading SARS-CoV-2, the virus that causes COVID-19. New variants of the virus spread more easily and quickly, particularly among young adults, which may lead to more cases of COVID-19 among college students this fall. An increase in the number of COVID-19 cases will strain healthcare resources and lead to more hospitalizations and potentially deaths. The best defenses against contracting COVID-19 and spreading the virus to others are vaccination and masking. On August 23, 2021, the U.S. Food and Drug Administration (FDA) fully approved the Pfizer COVID-19 vaccine. This means that the University of Minnesota requires students to be vaccinated for COVID-19 and students must complete this Student COVID-19 Immunization Vaccination Form by Oct. 8, 2021. Exemptions may be requested for religious or medical reasons. For resources about the vaccination and how to schedule an appointment, please refer to the University’s Get the Vax 2.0 initiative. When indoors, you are currently required to wear a face covering (mask) to protect the entire community of students, faculty members, and staff. Please wear your mask so that it covers both your nose and mouth. This will maintain a culture of safety to help protect all members of the community, and especially those who are immunocompromised and/or who are caretakers of others (e.g., young children) who are not yet vaccinated. Even though vaccinations are highly protective and required on campus, breakthrough infections do occur; therefore, indoor masking continues to be an important part of our layers of safeguard to keep the community safe and is one of our most important tools for ensuring sustained in-person learning. Both the CDC and MDH recommend that we ask ourselves every day if we have any COVID symptoms (including fever or chills, cough, shortness of breath or difficulty breathing, new loss of taste or smell, muscle aches or sore throat) and that if so we stay home and get tested, even if we're already vaccinated. I commit to doing my part to keep you and your colleagues safe by doing this, and I expect that you will too. If you experience COVID-19 symptoms or symptoms of any potentially infectious respiratory illness, you should stay home or in your residence hall room and not come to class or to campus. Please consult your healthcare provider about an appropriate course of action, and consult the M-test program for COVID testing resources. Absences related to COVID-19 symptoms, testing, or exposure, for yourself or your dependents, are excused absences and I will work with you to find the best course of action for missed work and course content. The above policies and guidelines are subject to change, since the University regularly updates pandemic guidelines in response to guidance from health professionals and in relation to the prevalence of the virus in our community.