CISC 3410 Artificial Intelligence
Basic Information and Requirements
- Instructor: Prof. Neng-Fa Zhou
- Class hours: MW 02:15-03:30PM (234 IA)
- Office hours: 5:00-6:00 Wednesday (room Ingersoll 1161)
- Reference Books and Web Sites:
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, such as Picat for constraint solving and planning, PRISM for probabilistic reasoning, and Keras for machine learning applications. Students are also encouraged to implement search, reasoning, and machine learning algorithms.
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 cisc3410 (AT) picat-lang.org. 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.
Picat, CSP, and Planning
- Introduction to AI (Chapter 1)
- Solving Problems by Searching (Chapters 3,5)
- Bayesian Networks
- Markov Decision Processes
- Learning Decision Trees
- Neural Networks
- Reinforcement Learning