01-02 LS&A Bulletin

Courses in Complex Systems (Division 348)

CMPLXSYS 501. An Introduction to Complex Systems.: (3).; This course covers a broad range of fundamental topics relevant to the study of complex systems. Topics covered include evolutionary systems, self-organized criticality, measures of complexity, approaches to modeling complex adaptive systems, and emergence. Authors covered include Holland, Axelrod, Kauffman, Bak, and Gell-Mann.
CMPLXSYS 510 / MATH 550. Introduction to Adaptive Systems.: Permission of instructor. Working knowledge of calculus, probability, and matrix algebra. (3).; Centers on the construction and use of agent-based adaptive models. Course begins with classical differential equation and game theory approaches, and then focuses on the theory and application of particular models of adaptive systems such as models of neural systems, genetic algorithms, classifier systems, and cellular automata.
CMPLXSYS 520 / PHYSICS 580 / MATH 552. Empirical Analysis of Nonlinear Systems.: Graduate standing and Enrollment in Certificate Program. (3).; The course begins with a very quick review of inference theory, probability and linear methods, followed by an even quicker review of nonlinear dynamics. The main body of the course is taken up with a critical discussion of a variety of nonlinear methods of empirical analysis. These include methods based on correlation integrals, as well as methods such as nonlinear prediction, singular-value decomposition, and DVS methods. A variety of nonlinear systems arestudied to illustrate the strengths and weaknesses of different methods. These include data sets form the physical, biological and social sciences as well as simulated data from simple mathematical systems.
CMPLXSYS 530. Computer Modeling of Complex Systems.: Enrollment in certificate program or permission of instructor. (3).; Introduces students to basic concepts, tools , and issues which arise using computers to model complex systems. Emphasis is placed on the modeling process itself, from model design through implementation to analyzing, documenting, and communicating results. Case studies of computer models of complex systems, including adaptive and non-adaptive complex systems drawn from economics, ecology, immunology, epidemiology, evolutionary biology, political science, and cognitive science.
CMPLXSYS 531. Basic Computing Skills for Programming Agent Based Models: (1-2).; This course covers the basic computing skills which are required for implementing again-based models using Swarm (and other similar packages) in a LINUX/UNIX environment, including (a) basic LINUX/UNIX commands, (b) basic programming concepts (variables, operators, flow-control), (c) creating simple C and objectiveC programs and (d) basic Object-Oriented Programming concepts. For students intending to take CSCS 530.
CMPLXSYS 541 / PHYSICS 413. Introduction to Nonlinear Dynamics and the Physics of Complexity.: Phys. 401. (3).; An introduction to non-linear science with an elementary treatment from the point of view of the physics of chaos and fractal growth.
CMPLXSYS 599. Independent Study of Complex Systems.: Graduate standing and permission of instructor. (1-3). (INDEPENDENT).; Directed readings or research in consultation with a member of the faculty in Complex Systems.
CMPLXSYS 899. Special Topics in Complex Systems.: Graduate standing. (1-4; 1-3 in the half-term). May be elected three times, for a maximum of nine credits.; Interdisciplinary special topics course offered on the subject of Complex Systems. The course will expose students to expertise, techniques, and ideas that they would not find elsewhere on campus. Taught by visiting interdisciplinary specialists who are in-residence at UM.

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