CSci 8551, Fall 2017: Syllabus

Lectures

Time Monday and Wednesday, 4:00-5:15
Room Keller 3-125
Instructor Dr. Maria Gini (gini@cs.umn.edu)
office hours: Monday 5:30pm-6:30pm; Wednesday 3:00pm-4:00pm and by appointment, in Keller 4-225C

Reading List

There is no textbook, we will read papers from a reading list that will be posted together with other class material on the Web page at http://www-users.cselabs.umn.edu/classes/Fall-2017/csci8551/.

Recommended readings:

UNITE videos

Streaming video archives of class meetings are available to students registered in the on-campus section of this course on a ten-day delay for the length of the semester.

Access these videos through the UNITE Media Portal with your University of Minnesota Internet I.D. and password (this is what you use to access your University of Minnesota email account).

If you need troubleshooting assistance with these streaming video archives use the UNITE Troubleshooting FAQ or Submit a Trouble Report to UNITE link found on all pages within the UNITE Media Portal.
Technical FAQ: http://www.unite.umn.edu/streamingvideopodcasts/faq.html UNITE Media Portal: https://www.unite.umn.edu (note the s in https)

Prerequisites

Basic knowledge of Artificial Intelligence. Specifically, you should have a general understanding of AI search algorithms, such as A*, and the use of heuristics. The first two chapters of the standard AI textbook provide a short introduction to the history of AI and to agents. Chapters 3, 4, and 5 cover the search algorithms.
Stuart Russell and Peter Norvig "Artificial Intelligence. A modern approach. 3rd Edition", Prentice-Hall, 2010. ISBN: 9780136042594

Course Objectives

We will examine theoretical foundations and current developments in intelligent agents. The collections of papers we will read will provide a broad perspective of the field. The study of agents presents a unique opportunity to integrate results from many diverse areas of research, such as Artificial Intelligence, robotics, knowledge representation, planning, machine learning, distributed systems, software engineering, and human-computer interaction.

Course Requirements

  • submit each week a short writeup (1-2 pages) on the most important pointsfor each required reading paper for the week and your reflections on them (2% each, total 24%).
    What is important in your writing is:
    1. Substance: include enough material in your writing. Start with a short summary of the paper, followed by your critical reflections on it. Note related work you are familiar with, connect what is in the paper with your research if relevant, think what could you do to extend the work presented or what you would do differently.
    2. Synthesis: put the information in your own words. Do not lift the main points from the paper, even if you quote them. Rewrite them in your own words.
    3. Critical reading: note any issue or problem you see in the paper. Feel free to address ease of reading, clarity, motivations, innovation, relevance, technical content, experimental setup, etc.
    4. Creativity: think what how you would things differently, where you could apply the methods presented, how you could extend them.
    The writeup has to be submitted by the start of the Monday's class on Moodle.
  • attend class and participate to class discussion (1% per class session, total 26%). Attendance is important but you need to participate to the discussion to get full credit.
  • present one of the papers from the reading list to the class. This includes giving a short presentation of 20-25 minutes that highlights the important ideas in the paper, covers some of its criical details, and connects the work to other related work in the same area or other papers already covered in class. You need to provide your presentation notes, and facilitate class discussion by posing questions for discussion (15%). The presentation will be evaluated on quality of presentation, quality of visual materials, coverage of the important points, quality of answers to questions, and ability to stimulate thinking.
  • do a project, individually or in a group of two, on a topic of your own choice related to the class and present briefly your results to the class at the end of the semester (35%). More details on what to submit and when will be available soon in the project page. You should plan on spending approximatively 50 hours on your project. The project is appropriate for Plan C.

    Academic Integrity

    All work submitted for this class must represent your own individual effort unless group work is explicitly allowed. Academic integrity and professional behaviors are expected from everyone in the class.

    Disabilities

    It is University policy to provide, on a flexible and individualized basis, reasonable accommodations to students who have documented disability conditions (e.g., physical, learning, psychiatric, vision, hearing, or systemic) that may affect their ability to participate in course activities or to meet course requirements. Students with disabilities are encouraged to contact Disability Services for a confidential discussion of their individual need for academic accommodations. Disability Services is located in Suite 180 McNamara Alumni Center, 200 Oak Street. Staff can be reached by calling 612-626-1333 voice or TTY, or on the web at http://ds.umn.edu/.
    Copyright: © 2017 by the Regents of the University of Minnesota
    Department of Computer Science and Engineering. All rights reserved.
    Comments to: Maria Gini
    Changes and corrections are in red.