EECS 594 - Introduction to Adaptive Systems
Section: 001
Term: WN 2012
Subject: Electrical Engineering and Computer Science (EECS)
Department: CoE Electrical Engineering and Computer Science
Requirements & Distribution:
Waitlist Capacity:
Advisory Prerequisites:
EECS 203, and MATH 425 or STAT 425.
Other Course Info:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Primary Instructor:

COURSE ORGANIZATION: This is a highly interactive class with students from all over campus. You will be expected to contribute to the class discussion and will be graded accordingly. There will be a final paper which you will present to the class.

TOPICS: Many of our most difficult contemporary problems depend upon an understanding of systems consisting of agents that adapt and learn: ecosystems, markets, language acquisition and evolution, political systems, the Internet, nervous systems, immune systems, reaction networks in biological cells, and so on. These systems, called complex adaptive systems (cas), exhibit properties such as "emergent" structures, "complex" conditional interactions, perpetual novelty in behavior, and diversity in agents (there is no "best" agent). Because of these properties, cas require novel techniques for analysis and understanding. This class will introduce and explore techniques, such as agent-based modeling, that have been most effective in helping us to explore and understand the behavior of cas.

The class aims to develop a range of ideas, examples, models, and intuitions that provide a deeper understanding of cas. All techniques will be fully developed in class, starting from elementary principles. The order of topics will depend partly upon particular interests of the class, but the following topics, at least, will be covered:

  1. Performance systems — sets of condition/action rules.
  2. Signal-passing systems — their pervasiveness from cell biology to language.
  3. Parallelism — systems with many rules active simultaneously.
  4. Agent-based models — models with multiple interacting agents.
  5. Credit assignment — strengthening stage-setting and predictive rules.
  6. Rule discovery — genetic algorithms.
  7. Building blocks — their role in everything from perception to invention.

Texts: HIDDEN ORDER (paperback) and EMERGENCE (paperback). Both published by Perseus Press and authored by J.H. Holland

Course Requirements:

No data submitted

Intended Audience:

PREREQUISITES: Either familiarity with programming (no particular language required), or a course in finite mathematics. All technical topics will be developed in class from first principles.

If you are an LSA Honors student, you can register for this course without permission of the instructor or Honors dept.

Class Format:

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EECS 594 - Introduction to Adaptive Systems
Schedule Listing
001 (LEC)
TuTh 9:00AM - 11:00AM
Note: Meets with Honors 493-001, Psych 447-001 and Psych 808-001.
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