Martin Zwick Course Information

SYSC 511: Systems Theory

SySc 511 surveys fundamental systems concepts and central aspects of systems theory. The course begins with an overview of the systems paradigm and the systems field as a whole. Topics then include introductions to set- and information-theoretic multivariate relations, dynamic systems, regulation and control, model representation and simulation; decision analysis, optimization, and game theory; artificial intelligence, complex adaptive systems. Readings draw from mathematics, the natural and social sciences, and the professional disciplines (e.g., engineering, business).

The course content derives both from "classical" general systems theory, cybernetics, and operations research as well as from more contemporary systems research which is organized around the themes of nonlinear dynamics, complexity, and adaptation.

SYSC 551: Discrete Multivariate Modeling

SySc 551 focuses on information theory as a modeling framework and as a tool for discrete multivariate analysis. The course presents set- and information-theoretic methods for studying static or dynamic (time series) relations among qualitative variables or among quantitative variables having unknown nonlinear relationships. In the ?general systems? literature, this is known as ?reconstructability analysis? (RA). RA overlaps partially with log-linear statistical techniques widely used in the social sciences; both are especially valuable in data-rich applications (but RA is not exclusively statistical). RA is highly relevant to the many interrelated "projects" which go under the names of data-mining, machine learning, knowledge discovery and representation, etc.

Applied to data analysis, RA allows the decomposition and compression of multivariate probability distributions (contingency tables) and set-theoretic relations (and mappings), as well as the composition of multiple distributions/relations. These methods are very general. They are valuable in the natural and social sciences and in engineering, business, or other professional fields whenever categorical variables are useful or, for quantitative variables, where linear models are inadequate. Applied to the conceptualization of "structure" (the relations between wholes and parts) and "complexity," these set- and information-theoretic ideas are foundational for systems science.

Discrete Multivariate Modeling II

SySc 510/610 will continue the presentation of DMM (SySc 551/651), and will focus on (a) projects and (b) advanced topics. In projects, students will either do either (i) an intensive analysis of some dataset or (ii) a software project that enhances the current set of RA tools. The advanced topics will include most (or all) of the following: state-based RA and k-systems analysis; RA loopless models with many variables ("dependency analysis"); identification with inconsistent data; set-theoretic RA and binary decision diagrams; intra-model analysis; modeling with latent variables; RA and genetic algorithms; Fourier-based RA techniques; binning; the OCCAM software package.

SYSC 552: Game Theory

Game theory involves the study of cooperation and competition, without regard to the particular entities involved, and issues of rationality associated with such phenomena. Sysc 552 presents the basic ideas of game theory, especially those concerning (a) 2-person zero-sum games, which the theory solves, and (b) 2- (or n_equivalent-) person nonzero-sum games, which have no general solution and which often exhibit paradoxical features. Of particular substantive interest are dilemmas of collective action, which characterize many social, economic, and political problems. Of particular methodological interest are simulation techniques used to extend game-theory into domains where analytical results are impossible.

Also covered are (c) 2-person cooperative games (bargaining & arbitration), which have alternative plausible solutions; (d) coalition theory (n_{non-equivalent}-person games), in which analysis is complex and limited; and (e) social choice theory, which reveals the difficulties in integrating individual preferences into collective decisions. Emphasis in the course is on the findings of game theory, especially as they apply to the social sciences, rather than on the purely technical aspects of the theory.

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.

SySc 557 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 521: Systems Philosophy

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.

SYSC 510: Systems Ideas & Sustainability

This course will examine systems ideas that bear on sustainability. These ideas come from graph theory, game and decision theory, and thermodynamics, and from systems-related theories in ecology, sociology, and history. The ideas shed light on the causes of sustainability problems and on the principles that might guide attempts to solve these problems.

The course is still under construction, so a syllabus is not yet available. In part, it will be an adaptation of SySc 521, Systems Philosophy, which presents a broad range of systems ideas, integrates them into a coherent framework, and organizes them around the theme of fundamental ¿problems,¿ that is, difficulties (imperfections, modes of failure) encountered by many systems of widely differing types. This new course (SIS) will focus on the more specific yet still quite diverse problems associated with sustainability, to which many systems ideas are relevant. Many of these ideas that will be presented in this course are mathematically-based, but these will be approached primarily at a conceptual level (with mathematical details provided as requested).

Readings yet to be selected; there will probably be a xeroxed reader obtainable at SmartCopy, 1915 SW 6th (227-6137).

Course work: term paper (25 double-spaced pages + bibliography); class participation; supplementary short writing assignments

Prerequisites: None, though some background in either systems ideas and/or sustainability will be helpful. This is a graduate course in Systems Science but undergraduates are welcome.

Guide to Martin Zwick's Courses

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Topics:

1. Degree of mathematical content and topic specialization of courses

2. Relevance of courses to different fields

3. Course scheduling

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Table 1. Degree of mathematical content and topic specialization of courses

SP: 510/610; ST: 511/611; AL: 557/657; DMM: 551/651; GT: 552/652

I am comparing the relative mathematical content only of my own courses; I'm not quantifying how mathematical my courses are compared to courses given by other faculty.

¹Although the Discrete Multivariate Modeling course is listed as having "high" mathematical content, it is accessible to social science students who have taken courses in probability and statistics. Calculus is not needed for DMM. Some prior exposure to set theory is helpful but not essential.

Systems Philosophy and Systems Theory are both survey courses. ST covers -- more mathematically -- some of the topics discussed in SP. In SP, the emphasis is on becoming familiar with concepts and the work in the course is writing a paper. ST, by contrast, is competence-oriented, and exams are used to evaluate knowledge gained. (Some other topics discussed in SP are presented in greater detail and more technically in Artificial Life.)

The full length courses of DMM and Game Theory give two of the SP/ST topics, namely (1) set- and information-theoretic analyses of multivariate relations and (2) game and decision theory, more extensive treatment. DMM and GT (and AL) can be taken without previously taking ST or SP, but this is easiest for students in mathematics, physical sciences, or engineering, or for social science students who are comfortable with quantitative methods. Students who like to encounter concepts or be given a general orientation before tackling mathematics should consider taking SP before other courses.

In bold are courses (AL, GT, DMM) that can provide a basis for dissertation research, i.e., there are past or current dissertations by SySc students based on the subject matter of these courses.

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Table 2. Relevance of courses to different fields

By "social sciences," I mean Psychology, Sociology, Economics, Political Science, Anthropology, Social Work, Urban Studies, etc. I include Engineering Management or Technology Management in "business."

²The indicated level of relevance for the different fields is an estimate based on an intuitive averaging over the contents of these fields. For some fields, GT and AL are listed as having low relevance, but this needs to be qualified by noting that Game Theory has some relevance to certain aspects of mathematics and engineering, and that some aspects of Artificial Life are quite relevant to the social sciences.

Note that the ideas and (especially the) methods taught in DMM are relevant to, and thus potentially useful in, virtually every field.

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Table 3. Course scheduling

Currently, these courses are offered in the quarters indicated. In bold are courses which are likely to continue to be offered in the quarters indicated. Courses not in bold might be given in different quarters in the future.