Introduction to Artificial Intelligence
Semester A 2014-2015 (Fall 2014)
* Under Construction *
BGU Computer Science Department
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. We will also briefly examine the currently hot topic of meta-reasoning in search.
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 2014-2015 (Fall 2014)
- Credits: 4
- Instructor: Prof. Solomon Eyal Shimony
- Grader: Michael Schneider (see grader's web page)
- Course scheduled at:
- Tuesday 16-18, building 90, room 237.
- Wednesday 14-16, building 90, room 123.
- Syllabus and requirements
- Midterm exams, (use of books and notes allowed):
- 1st midterm exam: Thursday, December 11 (2014), 17-19, Building 32, Room 307.
- 2nd midterm exam: Thursday, January 22 (2015), 17-19, Building 32, Room 307.
Note: Midterm to be held despite strike by administrative employees
Grading complete, results will be posted physically after 3PM Tuesday (room 216).
Office hours Wednesday (tomorrow) moved to 10-12 due to faculty meeting.
Example midterm from previous years.
definitions and algorithms for Bayes networks.
Environments and search (simplified, deterministic).
- Assignment 2: Adversarial games. Deadline: December 10. Postponed to December 15.
- Assignment 3:
Theoretical assignment on search and reasoning. Deadline: Tuesday, December 9, at 12 noon. Postponed due to multiple requests to
Wednesday, December 10, at 12 noon (strict!) .Solutions (available after deadline).
- Assignment B1:
Logical reasoning reasoning (Optional, bonus assignment).
- Assignment 4:
Probabilistic reasoning. Deadline: January 11, 2015.
- Assignment 5:
Partial observability - decision-making (Canadian Traveler Problem). Deadline: January 23, 2015.
- Assignment 6:
Exercise on planning, reasoning and decision making under uncertainty, and learning. Deadline: January 20, 2015.
- Example quiz and
- Lecture topics and notes.
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