Fall 2002 One Page Flyer

SySc 510/610: Systems Philosophy

This seminar style course focuses on systems ideas and related philosophical issues. It is organized around three themes:

  1. The nature and value of systems thinking
  2. Core systems concepts and their interrelationships
  3. The use of these concepts to illuminate the difficulties and hazards encountered by natural and social systems

For more information: Systems Philosophy Course Description

SySc 513: Systems Approach

Provides a practitioner-oriented introduction to systems, including:

  • observer dependencies & context
  • meta-systems & subsystems
  • value systems and associated optimization/sub-optimization
  • life-cycle project management
  • inquiring systems
  • learning organizations
  • multiple perspectives.

Also explores qualitative aspects systems analysis tools such as graphs, structural modeling, and dynamic modeling.

For more information: Systems Approach Course Description

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.

For more information: Course Overview on WebCT

SySc 575/675: AI: Neural Networks I

Neural networks is a computational and engineering methodology based on emulating how nature has implemented biological brain (in particular, the brain's massively parallel and learning aspects). As such, it holds promise for significant impact on how important classes of scientific and engineering problems are solved. The objective of the two-term sequence is to have the students obtain a working knowledge of this forefront technology.

This course covers basic ideas of the neural network (NN) methodology, a computing paradigm whose design is based on models taken from neurobiology and on the notion of "learning." A variety of NN architectures and associated computational algorithms for accomplishing learning are studied. Experiments with various of the available architectures are performed via a (commercial) simulation package. Students do a project on the simulator, or do a special programming project.

For more information, see the Course Flyer

SySc 510/610: Agent Based Simulation

This course focuses on the technical and theoretical aspects of agent-based programming. During this class students will learn how to use StarLogo to create agent-based models and use agent-based simulations in research and education. Reading assignments focus on the history and theories behind agent-based programming and the decentralized perspective.

For more information: http://www.webct.pdx.edu/public/sysc610abs/index.html