Spring 2005 One Page Flyer

SySc 512: Quantitative Methods of Systems Science

An introduction to the quantitative representation and investigation of systems with a focus that emphasizes tools more than applications. Topics include linear dynamics, optimization, and uncertainty. The level of presentation assumes familiarity and facility with calculus. Notions from linear algebra unify the topics and those notions will be presented. Required course work includes both calculations to be done on a computer (MATLAB or Octave will suffice) and calculations to be done by hand.

SySc 527/627: Discrete System Simulation

The mathematical basis for discrete system simulation (DSS) is probability theory and queuing theory. It is used extensively in the fields of operations research, civil engineering, industrial engineering, systems analysis, etc. Students learn how to use DSS to model systems of interest.

Emgt/SySc 553/653: Manufacturing System Simulation

The course focuses on using the ProModel discrete event simulation software to model manufacturing systems. Concepts include: a) overview of discrete system simulation and manufacturing simulation, b) data collection and prob. distributions, c) modeling material handling systems, d) job shop and production planning applications, and e) experimental design and output analysis. Relevant aspects of ProModel are also covered: locations, entities, processing logic, arrivals, path networks, resources, etc.

The course is designed to be of interest to students in Business, Engineering Management, Systems Science, Systems Engineering, and other programs; and to professionals in manufacturing, manufacturing engineering, and industrial engineering.

SySc 557: Artificial Life

"Artificial Life" (ALife) is a name given to theoretical, mathematical, and computationally "empirical" studies of phenomena commonly associated with "life," such as replication, metabolism, morphogenesis, learning, adaptation, and evolution. It focuses on the materiality-independent, i.e., abstract, bases of such phenomena. As such, it overlaps extensively with "theoretical biology" and, less extensively, with certain areas of physics and chemistry and the social sciences. It also raises important philosophical questions. It is part of a larger research program into "complex adaptive systems," one stream of contemporary systems theory.

In its intersection with computer science, ALife is the newest example of "the sciences of the artificial" (Herbert Simon). ALife is to life what AI is to intelligence. Christopher Langton writes that "Artificial Life ... complements the traditional biological sciences ... by attempting to synthesize life-like behaviors within computers and other artificial media." The purpose is twofold: to understand these phenomena better and to develop new computational technologies.

The course will sample the research literature in this field, and will be organized in a seminar format. Topics to be emphasized are: (1) discrete dynamics: cellular automata and random networks, (2) ecological & evolutionary dynamics, (3) genetic algorithm optimization and adaptation, (4) agent-based simulation. Other topics will include: artificial and real chemistry (metabolism, reproduction, & origin of life), "complex adaptive systems," autonomous agents, and philosophical issues.

SySc 610: Systems Approach to Research in Applied Psychology

Students are guided through a process of exploring how key systems-approach concepts shape research in applied psychology. Groups of students, using a topic of interest to them, will construct two alternative study designs employing the relevant systems-approach principles. Through class lecture and student-led interactive class presentations, faculty and students will explore the use of systems concepts in psychological theory and research and will assist students in critiquing and refining their own designs. Faculty will draw examples of research from the areas of applied psychology. Each student group will submit and present their study design projects during the term.