CSCI 630-01: Foundations of Intelligent Systems (Fall 2017)

Department of Computer Science, RIT (Fall 2017)
CSCI 630-01 Foundations of Intelligent Systems

Instructor: Prof. Richard Zanibbi ( rxzvcs(at) )
  Office Hrs (GOL-3551): Wed 11:15am-1:15pm, Fri. 2:30-3:25pm
  Lectures (GOL-3560): Mon, Wed, Fri 1:25-2:20pm

Teaching Assistant: Karan Jariwala (kkj1811(at)
Office Hrs (CS Tutoring Center): Tuesdays and Thursdays, 1-2pm

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Calendar Description

An introduction to the theories and algorithms used to create intelligent systems. Topics include search algorithms (e.g. A*, iterative deepening), logic, planning, knowledge representation, machine learning, and applications from areas such as computer vision, robotics, natural language processing, and expert systems. Programming assignments and oral/written summaries of research papers are required. Prerequisites: Completion of CSCI-603 or CSCI-602, and CSCI-604 or CSCI-605, and CSCI-660 or CSCI-661, all with grades of B or better. Prerequisite may also be satisfied by successful completion of CSCI-243 or 4003-334, and CSCI-262 or CSCI-263. Class 3, Credit 3 (Fall, Spring)

Course Outcomes

At the end of this course, students will be able to:

  • Discuss the history and implications of Artificial Intelligence research.
  • Describe attributes of search techniques and the situations in which they may be used.
  • Describe and apply techniques for automated learning.
  • Perform logical analysis by hand and through the use of logic programming.
  • Implement standard algorithms for intelligent systems.

Contacting the Instructor

If you cannot make my scheduled office hours and need to talk outside of class, please send email to set up an appointment. I try to respond within 24 hours to emails that I receive between Monday morning and noon on Fridays. Between Friday afternoon and Sunday evening I am often unable to respond until Monday morning. Please be aware that I may be unable to answer emails about course projects and assignments before the deadline if they are received less than 24 hours before they are due.

Teaching Assistant

The course will be supported by a teaching assistant, who will holding weekly office hours in which to discuss course material, including programming. The TA will grade assignments and programming projects using keys provided by the instructor; the instructor will grade exams, research writing assignments, and presentations. Questions regarding assigned grades should be directed to the course instructor, and not the TA.

Also, please do not disturb the TA outside of the TA office hours. Graduate TAs are busy people, just like you. If you have a question for the TA, and it is not office hours, please send email instead.

Course Text and Resources

The (required) course textbook is Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig (3rd edition). Additional resources are available through the Resources web page.

Grading Scheme

Assignments for the course will be completed by individual students. Programming projects and a research project will be completed by groups of two to three students.

  • 25% Assignments (5)
  • 30% Programming Projects (2)
  • 15% Group Research Project:
    • 10% Report (3-4 pages)
    • 5% Presentation (10 minutes)
  • 30% Exams:
    • 10% Midterm Examination (1 hr)
    • 20% Final Examination (2 hrs)


There will be five assignments, which will include a blend of written and (short) programming questions. Assignments will be posted one week before they are due.

Programming Projects

There will be two programming projects to complete, using Python (Python 3, specifically). They will be completed by teams of two to three students.

Presentations and Written Summaries of AI Applications

In the last two weeks of class, students will present applications of AI research in groups of two to three students, and write a brief summary. Topics will be selected from a set provided by the instructor on a first-come, first-serve basis. Presentations will be ten minutes long, including any questions. Groups will also write a three to four page summary on the assigned reading for their group. Students will have an opportunity to respond to instructor feedback on a draft before submitting the final version of their write-up.

Late Policy

Normally assignments and projects will be due for submission through MyCourses on Fridays at 11:59pm, and submission will no longer be accepted after Sundays at 11:59pm. For each day a deliverable is late, it will receive a 10% penalty (i.e., 10% penalty on Saturday, 20% penalty on Sunday). After Sunday at 11:59pm, submissions will receive a grade of 0.

CS Common Course Policies Include:

  • Rescheduling an Exam
  • Course Withdrawal
  • Disability Services
  • Academic Integrity