The primary objective of this course is to expose students to a diversity of techniques for aiding decision-making.  It emphasizes exercises that provide both experience with making decisions and data for analysis of decision-making.

Concepts of observation, factorization, open systems, possible worlds, state, function, boundary, constraint, stability, identity, simulation, and virtuality.  Models from measurement theory, regression, inferential statistics, nonparametrics, game theory, logic, algebra, computational languages, artificial intelligence, knowledge engineering, situated activity, and boundary mathematics.

These course notes are primarily experiential exercises that give rise to class discussion of the principles and difficulties of decision-making. The course follows an "experience then discuss" model rather than a "listen then repeat" model.

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