Description and Objective:
This course is an introductory survey of artificial intelligence. The course will cover the history, theory, and computational methods of artificial intelligence. Basic concepts include representation of knowledge and computational methods for reasoning. One or two application areas will be studied, to be selected from expert systems, robotics, computer vision, natural language understanding, and planning.

Prerequisites: Comp 15 and either MATH 22 or familiarity with both symbolic logic and basic probability theory.

Text:
The textbook for the course is Artificial Intelligence: A Modern Approach (3rd edition). Stuart Russell and Peter Norvig, Prentice Hall (2010) ISBN: 0-13-604259-7

Instructor:
Anselm Blumer
ablumer (at) cs dottufts dot edu
Halligan Hall, Room 214
Office Hours: Monday 1:30 - 2:30 and Tuesday 3 - 4 or by appointment.
Send an email suggesting some possible times for appointments.
Home page

Teaching assistant:
Andrew Pellegrini
Andrew.Pellegrini (at) tufts dot edu
Office hours in Halligan extension main room
Sunday 7-9 PM
Monday 1:30 - 4 PM
Tuesday 2:30 - 4 and 7 - 8:30 PM

Communication:
Students are encouraged to communicate frequently with the instructor regarding any issues with the course. Students are encouraged to use email and office hours frequently. Any announcements regarding the course will be made via the course webpage or in class so be sure to check it frequently and be sure to get material for any class you miss.

Homework:
Homework will be assigned regularly in the course. While reading assignments will not be directly assigned it is important that students use the textbook to supplement their understanding of the material presented in the lecture. The majority of the assignments will be written assignments due on Wednesdays at the beginning of class on the due date specified. This work can be handwritten with the assumption that these assignments are legible. (A student may be asked to type their assignments if grading is not possible.)

Late Homeowork:
Because of the size of the class and the amount of homework 20% of the total number of points for the assignment will be deducted per weekday. No homework will be accepted after one week.

Exams:
There will be in-class exams on March 6 and April 17 and an optional final on May 6 at 3:30, during the regularly scheduled final time. The final is cumulative. Exams are closed book and no electronic devices are allowed, but one 8.5 x 11 sheet of paper with notes on both sides can be brought to in-class exams and two such sheets for the final.

Grade Calculation:
The in-class exams will count for 25% each and homework will count for 50%. If the final is taken, the lower exam will be dropped, the other exam will count for 20% and the homework and final will each count for 40%. If the revised calculation results in a lower grade, the final will be ignored.

Feedback:
Your thoughts and concerns on this course are important. You are encouraged to give feedback to the instructor and teaching fellow throughout the term. As always students will be asked to fill out a course evaluation at the end of the term.

Academic Misconduct:
Students should read the Tufts brochure on academic integrity located at: http://uss.tufts.edu/studentaffairs/judicialaffairs/Academic%20Integrity.pdf

A few highlights are presented to emphasize importance:

Absolute adherence to the code of conduct is demanded of the instructor, teaching fellow, and students. This means that no matter the circumstance any misconduct will be reported to Tufts University.

While students are encouraged to discuss course materials, no collaboration is allowed on homework. Specifically you may discuss assignments and projects verbally, but must write up or work on the computer alone. In addition any discussion should be documented. An example on the homework would be "Thanks to Ray for helping me understand Kolmogorov complexity." Another important example is citing a source, this could be "This information was adapted from www.boston.com"

While computers enable easy copying and collaboration both with other students and materials from the Internet, it is possible to use these same computers to detect plagiarism and collaboration.

If any student does not understand these terms or any outlined in The Academic Code of Conduct it is his/her responsibility to talk to the instructor.