Instructor: Todd Hester
Department of Computer Science
office hour: Thursday from 10:30-11:30 AM or by appointment
office: ENS 32NE
email: todd AT cs.utexas.edu
office hours: Thursday from 3pm-4pm (or by appointment)
office: ENS 1 basement lab (a few steps opposite the elevator)
email: eladlieb AT cs.utexas.edu
office hours: Tuesday from 4pm-5pm (or by appointment)
office: ENS 1 basement lab (a few steps opposite the elevator)
email: patmac AT cs.utexas.edu
Good programming skills, preferably in C and/or C++. Some background in artificial intelligence is recommended but not essential.
Reading, written, and programming assignments will be updated on the
assignments page. A tentative schedule for the entire semester is posted. But the readings and exercises may change up until the Tuesday before they are due (1 week in advance).
You can go directly to the final project page. To see your grades go to Blackboard.
Please enroll in the class on Piazza.
Important class information may be sent to this list. It is the student's responsibility to be subscribed.
The foremost goal of this course is to expose the student to the full range of activities required of a real-life computer science researcher. It turns out that computer scientists rarely read textbooks, sit silently in lectures, work on programming assignments with correct and complete answers, or take exams. Rather, they
Most upper-division CS students have determined that they enjoy taking CS classes (or at least that they're relatively good at it). However, this determination may not be indicative of a propensity for computer science research. This course presents an opportunity for students to help decide whether they would enjoy going on to graduate school and an eventual career as a computer science researcher. In particular, students will be required to read published research papers, write brief reactions to them, participate in class discussions, propose and execute a solution to a challenging open-ended problem, and write about their work. They will be given an opportunity to collaborate with one other student on the final project.
The content of the course will be related to autonomous agents. In order to succeed, students will need to attain a mastery of the subject. However evaluation will be based primarily on the above activities. There will be no exams.
There is no generally accepted definition of artificial intelligence "agents." But practitioners know them when they see them. In loose terms, agents are programs that (i) sense their environment, (ii) make decisions about how to act based on these sensations, and (iii) then execute these actions. Autonomous agents do all three of these steps on their own, i.e. without a human in the loop. Multiagent systems are collections of multiple agents that interact with one another.
This course provides a broad introduction to autonomous agents with an emphasis on multiagent systems. Topics include
There will be incremental programming assignments leading to a final project, and ultimately a tournament competition in the RoboCup soccer simulator. Students will be encouraged to work in pairs on the final project.
The course also has a significant writing component and carries the writing flag. Brief written answers to questions based on the reading will be assigned weekly. There will be a project proposal halfway through the semester with an opportunity for revisions in the form of a progress report. Students will also be required to perform peer reviews on two classmates' progress reports. The grade for the final project will be based largely on the written report due at the end of the semester.
This course also carries the independent inquiry flag. As part of the goal of this course is to introduce the student to research, the students will be engaged in the process of inquiry. They will be required to generate ideas and programs, critically discuss ideas, and write and present their own ideas.
Participation in the class discussions will also form a significant part of the grade. Class meetings will consist of discussions based on assigned readings.
With respect to content, the goal of this course is to give the student an appreciation for the broad research topics currently being pursued in the field of autonomous agents and multiagent systems. By the end of the course, the student should be able to
The course is designed to present a solid entry point to the field of artificial intelligence. For those students with interest, it could possibly lead to subsequent research opportunities.
These deadlines are designed both to encourage you to do the readings before class and also to allow us to incorporate some of your responses into the class discussions.
If you turn in your assignment late, expect points to be deducted. No exceptions will be made for the written responses to readings-based questions (subject to the ``notice about missed work due to religious holy days'' below). For other assignments, extensions will be considered on a case-by-case basis, but in most cases they will not be granted.
For the penalties on responses to the readings see above (under course requirements). For other assignments, by default, 5 points (out of 100) will be deducted for lateness, plus an additional 1 point for every 24-hour period beyond 2 that the assignment is late. For example, an assignment due at 2pm on Tuesday will have 5 points deducted if it is turned in late but before 2pm on Thursday. It will have 6 points deducted if it is turned in by 2pm Friday, etc.
The greater the advance notice of a need for an extension, the greater the likelihood of leniency.
You are encouraged to discuss assignments with classmates. But all written work must be your own. And programming assignments must be your own except for 2-person teams on the final project. All work ideas, quotes, and code fragments that originate from elsewhere must be cited according to standard academic practice. Students caught cheating will automatically fail the course. If in doubt, look at the departmental guidelines and/or ask.
The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. To determine if you qualify, please contact the Dean of Students at 471-6529; 471-4641 TTY. If they certify your needs, I will work with you to make appropriate arrangements.
A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.
|programming assignment 1 due Thursday|
|programming assignment 2 due Thursday|
|programming assignment 3 due Thursday|
|4||9/25,27||Agent communication and Teamwork|
|5||10/2,4||RoboCup case studies|
|programming assignment 4 due Thursday|
|6||10/9,11||Swarms and self-organization|
|project proposal draft due Thursday|
|9||10/30,11/1||Game theory II|
|10||11/6,8||Distributed rational decision making|
|project progress report due Thursday|
|progress report peer review due Thursday|
|final project due Tuesday, report due Thursday|
|Final||12/17, 2-5pm, BUR 136||final tournament (oral project report)|
Slides from the classes as well as other resources are posted on the class resources page.
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