Introduction to Artificial Inteligence - Fall 2015

BGU Computer Science Department

Syllabus

The course will be heavily based on the book "Artificial Intelligence - A Modern Approach", by Stuart Russel and Peter Norvig. As the book covers at least a 2-semester course, we will only cover the basics and some selected topics, as follows (with the relevant book chapters listed in tandem):

  1. What is AI? Intelligent agents (chaps. 1, 2)
  2. Problem solving and search + game playing (chaps. 3, 4, 5, 7)
  3. Meta-reasoning in search (interleaved in other topics)
  4. Knowledge and Reasoning (chaps. 7, 8, 9, 10.3)
  5. Overview of planning (gloss on chapters 11, 12)*
  6. Handling uncertainty (chapters 13, 14, 16, 17)
  7. Learning (chapters 18.1-18.3, 20.5)

Chapters marked with an asterisk (*) are optional - depend on time constraints. See exact course plan and detailed chapters here.

Note that the course does NOT include or require study of an "AI-type", programming language. In order to handle the homework assignments, good knowledge of at least one programming language is assumed, and in addition some of the assignments may be easier to do using a symbolic language (such as LISP, SCHEME, or Prolog).

Bibliography

Course requirements

There will be approximately 4 programming assignments, and 2 theoretical assignments, which will comprise 40 to 50 percent of the course grade. In addition, there will be two mini-exams (BOHAN) one approximately at mid-term, another at the end of the semester, each worth approximately 25-30 percent of the final grade.

No cheating! You are required to get a non-zero grade on all assignments in order to pass the course. An unsubmitted assignment gets 1/100. An assignment too similar to someone else's assignment (i.e. cheating) gets you 0/100 and no credit in the course.

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