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Models in Science, SYSC 399U
University Studies
Cluster Course for Science in the Liberal Arts
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, and animal. To facilitate this exploration, the course is divided into three main sections.
The course provides both a conceptual understanding of how models are used in science and “hands on” experience conducting scientific inquiry using models as tools.
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Provides a practitioner-oriented introduction to systems, including:
Also explores qualitative aspects systems analysis tools such as graphs, structural modeling, and dynamic modeling.
For more information: Systems Approach Course Description
This seminar will consider some philosophical issues central to the systems field. Fundamental to these issues is Bunge's conception of systems science as a research program aimed at the construction of an exact and scientific metaphysics, that is, a set of concepts, models, and theories of broad generality and philosophical import, which are applicable to the sciences, and which are cast (or capable ultimately of being cast) in the exact language of mathematics.
The course will present a broad range of systems ideas (from information theory, game theory, thermodynamics, non-linear dynamics, decision theory, and many other areas) and attempt to integrate these ideas into a coherent framework. These ideas will be organized around the theme of fundamental "problems," that is, difficulties (imperfections, modes of failure) encountered by many systems of widely differing types. While most of these ideas are mathematically-based, they will be approached in this course primarily at a conceptual level (with mathematical details provided as requested). Many of these systems ideas derive from the natural sciences and engineering, but they apply as well to the social sciences and to fields of professional practice (business, the helping professions, etc.). It is primarily their relevance to the human domain--to individuals, groups, organizations, and societies ¿ and to technology which motivates this theoretical/philosophical inquiry. Certain of these ideas pertain also to the arts and humanities.
This course draws from the literature of general systems theory and cybernetics, which launched the systems research program, and from the literature of chaos, complexity, and complex adaptive systems which continues this program today. While the contemporary renaissance of systems theory has brought major advances, the older "classical" tradition of GST/cybernetics articulated the systems project in a deeper way. Seminal writings of both classical and contemporary systems scientists (e.g., Boulding, Deutsch, Emery & Trist, Jantsch, Laszlo, Bateson, Wiener, Holland, Gell-Mann, Crutchfield, Arthur) will be discussed.
Readings will be from (1) the manuscript of a book (working title: Elements and Relations) being written by the instructor, which attempts the integration spoken of above, (2) a collection of xeroxed articles and selections from books, and (3) a Scientific American Reader in Systems Theory & Complex Systems, all obtainable at SmartCopy, 1915 SW 6th (227-6137).
Course work: term paper (25 dbl.-sp. pages [non-mathematical papers]+ bibl.); class participation; supplementary short writing assignments
Prerequisites: graduate status in Systems Science or permission of instructor. This is a seminar course with limited enrollment, so SySc students have first priority.
Information on Systems Philosophy research
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: www.webct.pdx.edu/public/sysc529/
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: www.webct.pdx.edu/public/sysc610abs/
