CS4222 – Artificial Intelligence (Fall 2024)

Artificial Intelligence is the study of intelligent behavior of machines. Broadly speaking, this is understanding how to make machines and software that can reason, learn, and evolve like animals or humans.

AI has a long and interesting history that arose out of philosophical questions from antiquity and blossomed in the 1950s with the advent of electronic computers and computational research. In this course, we will study the basic ideas behind automated reasoning, heuristic search, representing knowledge effectively, and learning.

The course is structured into three units, with 4-6 topics in each unit. We will discuss each topic in lecture, there will be associated required reading, and possible a related lab or written assignment. Here is a tentative schedule for the semester:

This course addresses UMD campus student learning outcomes (SLOs), as well as CS education outcomes specified by the UMD Department of Computer Science and aligned with the standards put forth by the ABET accrediting board.

• SLO 1: Demonstrate competence in a major field
  • Students will gain knowledge of the core methods of artificial intelligence. They will be able to demonstrate knowledge of important search methods such as BFS, DFS, UCS, and A* search to solve a variety of problems.
• SLO 3: Think critically and creatively in seeking solutions to practical and theoretical problems.
  • Students will be able to formulate and solve constraint satisfaction problems with computer methods.
  • Students will be able to analyze, design and employ inference on knowledge representations using logical constructs on knowledge representation problems.
  • Students will be able to recognize different problems from the domain of AI, and be able to identify the most appropriate method for solving it.
  • Students will be able to discuss the use of probabilistic methods on problems with significant uncertainty.

There will be approximately five lab projects and five written homework assignments worth 20 points each. The labs are programming exercises where we will build concrete instances of algorithms discussed in class. We will use python for every programming exercise. No prior experience with python is necessary.

All assignments must be submitted by their stated due date.

We will periodically have in-class quizzes. Each quiz will give you a chance to demonstrate what you have learned and what concepts are still hazy.

Another goal of the quizzes is to encourage participation. Therefore, we will not announce quizzes ahead of time. Furthermore, we will usually go over the quiz together immediately afterwards. Because of this, we will not have make-up quizzes. However, to get you out of unforeseen circumstances, I will automatically drop the two lowest quiz scores.

The quizzes will count toward your participation grade, which makes up roughly 10% of your total grade.

There will be two midterm exams, worth 100 points each and a final exam worth 200 points.

Both midterm exams are closed book, and the final exam will be comprehensive. Exams will not be given early, and makeups must be justified by dire circumstances described to the instructor before the time of the exam. It is Department of Computer Science policy not to return final exams, however they are kept and you can look at your exam in the instructor's office. The UMD Final Examination Policy web page explains the UMD policy about having more than two final exams on a single day, among other things.

Final grades are based on total points distributed approximately as follows:

1. Assignments and participation (approx. 250 points)
2. Midterm Exams (200 points)
3. Final Exam (200 points)

Appropriate classroom conduct promotes an environment of academic achievement and integrity. Disruptive classroom behavior that substantially or repeatedly interrupts either the instructor's ability to teach, or student learning, is prohibited. Students are expected to adhere to the Board of Regents Policy.

Academic dishonesty tarnishes UMD’s reputation and discredits the accomplishments of students. Academic dishonesty is regarded as a serious offense by all members of the academic community.

Taking notes is a means of recording information but more importantly of personally absorbing and integrating the educational experience. However, broadly disseminating class notes beyond the classroom community or accepting compensation for taking and distributing classroom notes undermines instructor interests in their intellectual work product while not substantially furthering instructor and student interests in effective learning.

Students are expected to attend all scheduled class meetings. It is the responsibility of students to plan their schedules to avoid excessive conflict with course requirements. However, there are legitimate circumstances that lead to excused student absence from the classroom. These are subpoenas, jury duty, military duty, religious observances, illness, bereavement, and NCAA varsity intercollegiate athletics.

All 1xxx-5xxx courses offered for undergraduate credit should include a final graded component or end of term evaluation that assesses the level of student achievement of one or more course objectives. All final graded components are to be administered or due at the time and place according to the final exam schedule and not during the last week of class.

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Thoughtful dialog is a cornerstone of higher education. This expectation is upheld in the University of Minnesota's Board of Regents Policy: Academic Freedom and Responsibility, which says in part:

SECTION II. ACADEMIC FREEDOM. Academic freedom is the freedom, without institutional discipline or restraint, to discuss all relevant matters in the classroom, to explore all avenues of scholarship, research, and creative expression, and to speak or write on matters of public concern as well as on matters related to professional duties and the functioning of the University.