CISC 3410 Artificial Intelligence


Basic Information and Requirements

Topics

The course covers several major topics in AI, including problem solving, search, logic, probabilistic reasoning, and machine learning. The focus is on algorithms and tools for implementing AI agents that receive percepts from the environment and perform actions. This is a hands-on course, and students will explore the use of several high-level tools for solving AI problems. Students are also encouraged to implement search, reasoning, and machine learning algorithms.

Homework assignments

There will be one homework assignment every week. Unless notified otherwise, the homework is due in one week after it is assigned. Please email your homework to nzhou (AT) brooklyn.cuny.edu. Please write your name, student ID, and the number of the assignment in the subject, and include your writings and codes in the body of the email. Sample answers to the programming questions will be given and selected questions will be reviewed in class. There will be a one-point deduction for each missing homework or late submitted homework. The total deduction will not exceed 10 points.

Exams and Grading

There will one midterm exam and one accumulative final exam, both closed-book. The midterm accounts for 30%, the final accounts for 40%, and the remaining 30% of the grade will be based on homework, quizzes, and projects.

Course Outline

  1. Introduction to AI (Chapter 1)
  2. Solving Problems by Searching (Chapters 3,5)
  3. Picat, CSP, and Planning
  4. Probabilistic Reasoning
  5. Machine Learning