CS 463G Artificial Intelligence Syllabus

Class page

Time and Place: 10:00 am - 10:50 am, 263 FPAT

Professor: Dr. J. Goldsmith
Office: 311 Marksbury Building, Phone: 257-4245 (email is more reliable)
Office Hours: TBA and by appointment. Email questions strongly encouraged and answered.

Course Description:

The topics covered in this course will be:

• intelligent agents
  
• search and game-playing
  
• logical systems
  
• planning systems
  
• uncertainty---probability theory, inference, and decision theory
  

Prereqs: CS 315 and CS 375, and engineering or graduate standing. You should know how to program, be familiar with basic algorithms and data structures, especially for graphs and trees, and be familiar with propositional and predicate logic.

Textbook: Artificial Intelligence: A Modern Approach, 3rd Edition by Stuart Russell and Peter Norvig. Prentice Hall, 2009.

Grading:

There will be assignments approximately every other week, due Fridays at the beginning of class. Assignments will be posted on the web two weeks prior to the due date. The lowest homework grade will be dropped. Illegible work will not be graded. Plagiarized work will be penalized for all parties, according to University regulations. There will be occasional short writing assignments worth 1 point each, on the ethical, professional, personal, and societal impacts of AI. There will be one midterm and one final. In addition, you will be expected to post occasionally to an online forum, and to answer questions on that forum.

Assignments (problems and programs) will be 60% of your grade, postings will be 8%, the midterm project will be 12% and the final 15%, and occasional writings 5%.

The midterm project will be completed by October 10th; a project proposal is due September 12th, by 10 AM. The final project is due by December 12th at 9 AM, although any in-class presentations must be scheduled during a class period. The final project proposal is due Monday, November 7.

Those taking CS 463G for graduate credit (in any department except CS) will have the same assignments, but the lowest grade will not be dropped, and the cutoff for an A will be 85%, with 10% stepdowns per letter grade. paper or presentation.

READ THIS:

Attendance in class and section is very strongly encouraged.

You are encouraged to discuss homework problems, AS LONG AS YOU GIVE CREDIT TO WHOMEVER DISCUSSED THEM WITH YOU AT THE TOP OF YOUR HOMEWORK. You are strongly discouraged from seeking solutions online; if you do, YOU MUST CITE ANY SOURCES EXPLICITLY FOR EACH PROBLEM FOR WHICH YOU FOUND AN OUTSIDE SOURCE. Copying of homework from other students or from other sources is strictly prohibited. Obtaining a solution from another source without citing the source is plagiarism. The first instance of plagiarism will result in an un-droppable 0 on the homework. That typically drops you one letter grade. The second instance will become part of your permanent UK record, and can result in expulsion from the program.

You are encouraged to visit Dr. Goldsmith or the TA in their office hours or to send them email at any time if you are stuck on homework problems. You do not need an appointment for regularly scheduled hours. Email sent late Thursday night probably won't be answered in a timely fashion. PLAN AHEAD.

Outcomes and assessments

Students will learn basic concepts in logic and artificial intelligence. In particular, the student will be able to:

37. use current techniques, skills, and tools necessary for computing practices;
38. apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices;
39. understand search algorithms;
40. analyze games;
41. use logic to represent and reason about domain knowledge;
42. use Bayesian networks to represent and reason about domain knowledge;
43. model and solve planning problems;
44. understand the relevance of Artificial Intelligence to the real world;
45. program in a declarative programming language;
46. improve her/his ability to analyze a problem, and identify and define the computing requirements appropriate to its solution;
47. improve her/his ability to design, implement and evaluate a computer-based system, process, component, or program to meet desired needs.

Week by Week Course Outline:


Date	Topic	Chapter	Assignment
	INTRODUCTION
Aug. 24-6	Intro to course, AI, agents	1	Short Writing Assignment
	SEARCH
Aug. 29-Sept. 2	Agents, uninformed search	2,3	Puzzle, part 1
Sept. 5-9	Informed search	3,4	Puzzle, part 2
Sept. 12	MIDTERM PROJECT PROPOSAL DUE BY EMAIL
Sept. 12-16	Search heuristics; intro to SAT
Sept. 19-23	SAT algorithms, constraint satisfaction		SAT programs
Sept. 26-30	Games (minimax)	5
Oct. 3	No class
Oct. 5-7	Alpha-beta pruning, expectimax, intro to the Wumpus	5	Short writing assignment
Oct. 10	MIDTERM PROJECT DUE
	LOGICAL SYSTEMS
Oct. 10,14	Logic, reasoning, proofs, Wumpus world, situation calculus	7, 8	Short writing assignment
Oct. 12	No class
Oct. 17-21	Inference, resolution, Prolog	9	First Prolog program
	PLANNING AND UNCERTAINTY
Oct. 24-28	Planning	11	Second Prolog program
Oct. 31-Nov. 4	Uncertainty: Probability theory, Naive Bayes classifiers	13	Short writing assignment
Nov. 7	FINAL PROJECT PROPOSAL DUE BY EMAIL
Nov. 7-11	Bayesian networks	14-17	MCMC Program
Nov. 14-18	Planning under uncertainty
Nov. 21	Preferences		Short writing assignment
Nov. 22-25	THANKSGIVING BREAK (Class does not meet)
Nov. 28-Dec. 2	Machine learning	18	MDP/RL program
	Stanford ML lectures
Dec. 5-9	Ethics, Topics in AI, Review	20
Dec. 12	FINAL PROJECT DUE: 9 AM MONDAY, DEC. 12

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