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Courses One Page Flyer Fall 2012

SYSC 346U (also CS 346U) Exploring Complexity in Science and Technology

Freedom Privacy and Technology Cluster

Much of our scientific knowledge is based on two seemingly reasonable assumptions: 1) if we understand the parts of a system, we will understand the whole, and 2) small changes to a systems will have small effects, and big changes will have big effects. These assumptions turn out to be inadequate for many of the complex systems we interact with everyday (e.g. the weather, the economy, our biological environment, and the many social networks to which we belong). The goal of this course is to explore some of the most interesting and useful concepts behind the behavior of complex systems (without getting too bogged down in the scientific and mathematical details).


SYSC 399U, Models in Science

Meets Universitiy Studies Cluster Course Requirements

Science in the Liberal Arts and Knowledge, Reason and Understanding

This interdisciplinary course focuses on the role of models in scientific inquiry. Students explore how scientists from a variety of disciplines use different types of models, including physical (scale), mathematical (analytic and numeric), agent-based, animal, and social network. To facilitate this exploration, the course is divided into three main sections.

  1. Definition: We compare different definitions of "Science," "the Scientific Method," and "model." Here we also look briefly at what philosophers of science have said about how models fit into scientific inquiry.
  2. Analysis: We critically analyze a variety of models used in research from different disciplines. We will play with multiple types of (already constructed) computer simulation models to get a feel for how they can be used scientifically. We will discuss the strengths and weaknesses of modeling (in general) as a tool for posing and answering scientific questions. And we will identify modeling techniques that are best suited for answering different types of scientific questions.
  3. Synthesis: Students write a term paper where they either (1) identify a scientific question of interest and design a research project that uses scientific modeling to test it, (2) identify a field that could be furthered with scientific modeling and describe how this could be done, or (3) describe how scientific modeling is currently being used in a field of interest to relate scientific inquiry to a real-world problem.

The course provides both a conceptual understanding of how models are used in science and "hands on" experience exploring scientific inquiry using models as tools.


SySc 510: Data Mining with Information Theory

 

 

 



SySc 525/625: 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.pdx.edu/sysc/courses-sysc-525625-agent-based-simulation


SySc 529/629: Business Process Modeling & Simulation

The primary emphasis is on using discrete system models to analyze administrative, decision-making, product development, manufacturing, and service delivery processes. Discrete system models characterize the system as a flow of entities that enter and move through various processes and queues according to probability functions specified by the modeler. Monte Carlo sampling is used to calculate statistical measures of system performance, such as throughput, average queue length, resource utilization, etc. Some processes may also exhibit continuous characteristics, in which case continuous model constructs may be deployed. Continuous system models utilize the numerical integration of differential equations to simulate behavior over time. Such models are often used for studying the systems containing feedback loops, where the outputs are "fed back" and compared with control inputs. Process measurement and the unique challenges of modeling the software development process will also be covered in some detail.

For more information: http://www.pdx.edu/sysc/courses-sysc-529629-business-process-modeling-simulation