Description of the course

Artificial intelligence (AI) has recently regained the limelight, as the human world chess champion was beaten by Deep Blue, a program written by a team of researchers and programmers from IBM. Even more recently, a "re-match" against a distributed machine in Jerusalem also favored a computer program. In the more difficult field of partial information and chance games, such as Poker, AI programs now hold their own against human champions, as exhibited in a competition held during AAAI-2008. In the even more difficult field of automated robotics, a nearly fully autonomous car has recently (2012) been successful in road tests in the Western USA (Google driverless car). Other true AI applications are also on the rise, from expert systems for diagnosis and advice, through increasingly intelligent robots, to intelligent and autonomous www agents.

This course deals with the issues of defining intelligence and rationality in an agent, various methods of formalizing them, and models for representing and using knowledge. In specific topics, mainly search, logical reasoning, probabilistic reasoning, and decision-making under uncertainty, the course will focus all the way down to the algorithm level, in order to provide some hands-on experience with programming artificially intelligent agents.

This course now has 2 numbers, one as an undergraduate course, and one as a graduate course. These are both the same course although some details in assigmnents (e.g. bonus assignments, etc.) may be slightly different. Significant weight will be assigned to examining some open reasearch problems in some sub-fields of AI, especially in the graduate part of the course.

Course data and information pointers

• Course Reference: Artificial Intelligence (202-2-5661: graduate course, 202-1-5151: undergraduate course) - Semester A 2013-2014 (Fall 2013)
• Credits: 4
• Instructor: Prof. Solomon Eyal Shimony
• Graders: Raz Nissim, Evgeny Goldshtein
• Course scheduled at:
  1. Monday 14-16, building 34, room 203.
  2. Wednesday 12-14, building 35, room 310.
• Syllabus and requirements
• Midterm exams, (use of books and notes allowed):
  • 1st midterm exam: Thursday, December 5, 17-19. Building 32, room 307.
  • 2nd midterm exam: Thursday, January 16, 17-19. Building 35, room 211.
  • Example midterm from previous years.
• Some additional definitions and algorithms for Bayes networks.
• Assignments:
  1. Assignment 1: Environments and search (simplified, deterministic).
  2. Assignment 2: Adversarial games. Deadline: postponed due to assignment 3, midterm, and other reasons. New final deadline: December 14, at 11 AM.
  3. Assignment 3: Theoretical assignment on search and reasoning. Deadline: December 3 (strict!). Solutions.
  4. Assignment B1: Logical reasoning reasoning (Optional, bonus assignment).
  5. Assignment 4: Probabilistic reasoning. Deadline: January 2. (Postponed to January 9)
  6. Assignment 5: Partial observability - decision-making (Canadian Traveler Problem).
  7. Assignment 6: Exercise on planning, reasoning and decision making under uncertainty, and learning. Deadline: January 15, 2014, at 12 noon, solo submission. (Modified, due to error in day of week in assignment, since it said "Wednesday Jan 14").Solutions.
• Example quiz and Answers
• Lecture topics and notes.

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