COSC 6368 --- Artificial Intelligence Fall 2017 ( Dr. Eick )

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Basic Course Information

2017 COSC 6368 Syllabus
class meets: TU/TH 2:30-4p
class room: SEC 202
Instructor: Dr. Christoph F. Eick
office hours (573 PGH): TU 11:15-12:30p TH 4-4:45p
TA: Reza Fathi
TA office hour: TU noon-1p and TH 1-2p in 313 PGH
TA Email:
Reza's 6368 Webpage
office: PGH 313

cancelled classes: none at the moment
makeup classes: none at the moment
lectures taught by others:

Topics Covered in COSC 6368

The course will give an introduction to AI and it will cover Problem Solving (covering chapter 3, 4 in part, 5, and 6 in part, centering on uninformed and informed search , adversarial search and games, A*, alpha-beta search, evolutionary computing, game theory (chapter 17 and other matrial), and constraint satisfaction problems, discussion course Project 1)), Planning(covering chapters 10 and 11 in part), Learning (covering learning from examples (chapter 18), deep learning (extra material) and reinforcement learning (chapter 21, chapter17 in part;), Discussion Project2), Reasoning and Learning in Uncertain Environments (covers chapters 13, 14, 15 in part, and 20 in part, centering on ?basics? in probabilistic reasoning, na?ve Bayesian approaches, belief networks and hidden markov models (HMM)) and might, if enough time might briefly discuss Robotics, Philosophical Foundations of AI. The course will cover Chapter 1, 2, 3, 4, 5, 6, 10, 11, 13, 14, 15, 17, 18, 20, 21, and might, if enough time, partially cover Chapters 25, and 26 of the Stuart Russel & Peter Norvig book.

Course Materials

Required Text:
S. Russell and P. Norvig, Artificial Intelligence, A Modern Approach, Third Edition,
Prentice Hall/Allyn&Bacon, 2010,
Link to Textbook Homepage.

News COSC 6368 Fall 2017

Results of the Nov. 28 Questionnaire

Maybe, due to Dr. Vilalta's final exam on Nov. 29, and only 17 students filled out the questionnaire; here are the findings:


Students are expected to have the following background:

The prerequisites for the class are important, but only up to a point. The real prerequisite for this course is the ability to solve abstract problems, to understand nontrivial algorithms, and to have basic programming and system development skills. To some people these skills come by more easily, whereas others get them by taking the corresponding classes. If you feel that you have these skills, you can easily make up for the prerequisites on your own.

2017 COSC 6368 Student Presentations

Each student will either participate in a presentation or submit Homework2; we allocated only approx. 3 minutes for each student. Presentations will be given by groups of (2)3-4 students. Presentations will discuss general AI topics; others will conduct a search for things that are useful for the AI course and summarize their findings; others will demo AI tools, AI applications or report about AI contests.

Advice on the presentations themselves: Practice your presentation to make sure that you stay within the time-limit associated with your presentation. Each group member should present a part of the presentation! Finally, groups should introduce their members at the beginning of the presnentation and the first slide of the presentation should contain the names and a photo of the presenters, the presentation title, and whatever else you like to put on the first slide!

2017 COSC 6368 Presentation Schedule

September 21, 3:34p: #1: Suchismitha Vedala, Roopa Reddy Rajala and Charan Teja Sakhamuri: About the International Automated Negotiating Agent Competition (11 minutes).

September 28, 3:25p: #2: Kinjal Kotadia, Manasvi Thakkar, Maksim Egorov and Ayzha Ward: Presentation and Evaluation of the AAAI 2016 Best Paper Award Paper Bidirectional Search That is Guaranteed to Meet in the Middle (13 minutes, followed by a 7 minute discussion of the paper)

October 3, 3:30p: #3: Michael Bremner, Feng Guo, Xin Zhou and Ai Zhuo: Angry Bird AI Competition (13 minutes)

October 31, 3:33p: #4: Shah,Ashna Milind, Hoang,Huy Thai and Banerjee, Romita: AI Planning Tools (11 minutes)

November 16, 3:20p: #5: Lavanya,s.s; Yashwant, Jyothi and Kiranvarma: Outwitting Poachers with AI (13 minutes; and

November 16, 3:33p: #6: Arjun Subramanyam Varalakshmi, Qian Qiu and Chonghua Li: Mastering the game of Go without Human Knowledge (11 minutes)

November 28, 3:20p: #7: Akhil Talari, Mohit Kaduskar, Navya Doddapaneni: "Artificial Intelligence for Speech Recognition" (11 minutes).

#8: November 28: 3:32p: Konreddy,Deepika Reddy, Priscilla Roy Imandi, Eric Jiang and Abheesta Reddy: "What does Corporate America think about AI" (13 minutes).

#9: November 30, 2:40p: Goutam Venkatesh, Siva Uday Sampreeth Chebolu, and Dinesh Reddy Bethi: "On Humonoid Robots" (11 minutes).

#10: November 30, 2:52p: Anusha Nemilidinne, Harshitha Thallaparthi, and Chethana Dukkipati: "Google Street View" (11 minutes).


The course will have a midterm and a final exam, Students will be responsible for material covered in the lectures and assigned in the readings. All homeworks and project reports are due at the date specified. No late submissions will be accepted after the due date. This policy will be strictly enforced.

Translation number to letter grades:
A:100-90 A-:90-86 B+:86-82 B:82-77 B-:77-74 C+:74-70
C: 70-66 C-:66-62 D+:62-58 D:58-54 D-:54-50 F: 50-0

Only machine written solutions to homeworks and project reports are accepted. Be aware of the fact that our only source of information is what you have turned in. If we are not capable to understand your approach or solution, you will receive a low score. Moreover, students should not throw away returned assignments or tests.

Students may discuss course material and homeworks, but must take special care to discern the difference between collaborating in order to increase understanding of course materials and collaborating on the homework / course project itself. We encourage students to help each other understand course material to clarify the meaning of homework problems or to discuss problem-solving strategies, but it is not permissible for one student to help or be helped by another student in working through homework problems and in the course project. If, in discussing course materials and problems, students believe that their like-mindedness from such discussions could be construed as collaboration on their assignments, students must cite each other, briefly explaining the extent of their collaboration. Any assistance that is not given proper citation may be considered a violation of the Honor Code, and might result in grade reduction, obtaining a grade of F in the course, and in further prosecution.

2016 Course Projects and Homeworks

Specification Course Project1 (Individual Project; last updated on September 26; due on Th., October 6, 11p; Project1 Training Benchmark)

Homework1 (individual homework; due on Mo., October 17, 11p)

Project2: Learning Paths from Feedback Using Q-Learning (Group Project, PD-World; 2016 Project2 Groups; due on Nov. 19, 11p)
Homework2 (individual homework, due Nov. 30, 11p; except problem 6)

2016 Course Exams and Reviews

Review1 October 18, 2016
Review List Midterm Exam October 25, 2016
Review2 on December 1, 2016 (More solutions)
Review List Final Exam December 8, 2016, 2p

Previous Course Exams


Review Sheet for 2001 Midterm Exam
2004 Midterm Exam with some Solutions
2016 Midterm Exam with Solution Sketches

Final Exam

COSC 6368 2017 Final Exam Fall with Solution Sketches (in Word)
COSC 6368 Final Exam Fall 1999 (in Word)
COSC 6368 Final Exam Fall 2001 (in Word)
Fall 1999 AI PhD Qualifying Exam (in html)
last updated: December 14, 2017, 11p.

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