COURSE DESCRIPTION:
CS652 is a graduate level course (undergraduates may be admitted with written permission from the instructor). The course is designed to provide an opportunity for advanced treatment both of evolutionary (population-based) algorithms as well as emergent and adaptive computational architectures. Material is taken from readings of published research.

COURSE PREREQUISITES:
The most useful courses to have taken prior to this one are one or both of CS550 and CS552. These courses, especially 550, provide a backdrop against which these more modern techniques are contrasted. Students who have not taken either of these should contact the instructor to discuss their preparedness.

COURSE CONTENT:
Artificial intelligence research has moved in the past decade more deeply into approaches that are biologically inspired. This began after the engineering success of neural networks and has given rise to several interesting paradigms for producing computational intelligence. Approximately the first third of the semester will be devoted to the study of evolutionary (population-based) approaches. This includes genetic algorithms but goes beyond as well. Other focii will be cellular automata, swarm and ant-colony algorithms. The middle third of the semester will be devoted to the very young field of artificial immune systems. The final third of the semester will be an investigation of efforts to imbue programs with adaptive, autonomous behavior. After looking at a few different approaches, we will focus on various versions of an architecture first articulated by Hofstadter and Mitchell in the Copycat project.

COURSE TEXTS:
CS652 Emergent and Adaptive Computation ed. by Joseph Lewis, READER from Montezuma Publishing 2009, available from the SDSU bookstore
Complexity: Life at the Edge of Chaos 2nd ed. by Roger Lewin, University of Chicago Press 1999, available from the SDSU bookstore and elsewhere
Other readings will be made available during the semester.

CLASSROOM POLICIES:
  Attendance
This is a graduate level course. No formal attempt to measure your attendance will be made (other than during the initial crashing period). Of course, attendance and participation are considered important parts of your learning experience. The assessment (exams and projects) will demonstrate an expectation that you have been regularly in attendance and keeping up with the material. It is to your advantage to do so.
  Tardiness
Some students, due to work or other external situations, may be unable to arrive at the beginning of class or may have to leave before it has concluded. Also, unforeseen difficulties occasionally arise which force tardiness or the need to leave early. In these situations, please enter or leave the classroom quietly and respectfully. Sitting near an exit is a good idea. It is the responsibility of students in any of these situations to discover what material was covered.
  Collaboration
Students are welcome to study together; discussing algorithms, techniques, readings, etc. can be a fruitful way to learn. However, for individual or pair assignments, students are required, after developing ideas together with others, to WRITE THEIR IDEAS INDIVIDUALLY OR IN THEIR TEAM ONLY. Work that is obviously copied between individuals/teams will be considered plagiarism. If all or a substantial portion of your submitted written work can be found in online sources you will fail the course. Your writing should be your own.
  Dishonesty
The SDSU course catalog addresses cheating and plagiarism and other forms of academic misconduct. Instances of plagiarism will be referred to the Office of Judicial Procedures. Students who engage in such behavior not only jeopardizes their positions at SDSU, but interfere with their own learning, which is one important reason for being here. Please don't do it.
  Cell Phones
Please show the instructor and (more impactfully) your fellow students the same respect you wish others would show at a theatre, library, etc. with their cell phones. Before entering class, turn it off or set it to silent ring! If you must answer, leave the classroom quietly before beginning your conversation.
  Crashing
The final course size will be allowed to reach approximately 110 to 115 percent of its original closed size (in this case, 40), depending on seat availability in the assigned room. The number of students allowed to add will depend, therefore, on the number of seats emptied by those who drop or are no-shows for the first 2 weeks. Those who wish to add should continue to attend class from the first day on. At the end of two weeks, when the number of available seats is known, those who have continued to attend will be considered for adding. If that number still exceeds the available seats, the determination will be made as a function of the following criteria, roughly in order of significance: having the required prerequisites and/or possessing sufficient background, graduate vs. undergraduate status, in some cases order-of-request (including contact with the instructor prior to the semester), and finally, if these are not sufficient, random drawing.

STUDENT ASSESSMENT:
Student assessment will be based on three exams, two projects and a series of response writings to the readings. Details for the assessment of papers and exams will be discussed during the semester. Below is a breakdown that indicates how these assessments will be combined into a final course grade. Grading is an evolving endeavor, subjective and approximate at best. Also, student performance can be subject to many influences and skill differences. Respecting this, certain heuristics will be followed. As an example, generally high performance punctuated by lower performance in one particular domain will typically be assessed in favor of the higher. As a baseline, no student will ever receive a grade that is lower than her average as weighted below. Letter grades will be assigned to grade ranges based on the scores of the class as a whole. This will generally follow closely the familiar 10 point ranges of 90,80,70,60 for A,B,C, and D. If you have questions or concerns at any point about your performance in the course, you are strongly encouraged to visit the instructor.

	Project Paper ----------------------------------30%
        Response Writings ------------------------------10%
	Exam I -----------------------------------------20%
	Exam II ----------------------------------------20%
	Exam III ---------------------------------------20%