Sample Curriculum:

Epistemology, Scientific Method, and Automated Discovery


Epistemology, Scientific Methodology, and Automated learning and discovery is one of the major research thrusts of the department, with active involvement from Nobel Laureate Herb Simon, Teddy Seidenfeld, Clark Glymour, Peter Spirtes, Richard Scheines, Kevin Kelly, and Horacio Arlo-Costa. The department's breadth of coverage in this area is unique among Philosophy departments in the nation, running the gamut from cognitive models of learning and problem solving, automated discovery of causal models, foundations of statistical inference, belief revision theory, and formal learning theory. The faculty's overlapping interests in this area place students in a unique position to make novel theoretical and practical contributions to traditional epistemological issues.

The department's broad commitment to this research area is buttressed by its close association with the university's Department of Statistics, the Center for Applied Learning and Discovery and by the university's nationally preeminent Computer Science programs in artificial intelligence and machine learning.

The TETRAD project for causal inference from statistical data has earned many research grants providing the opportunity for students to do genuine research on a project in computatioanl epistemology with real world applications.


Defended Ph.D. Dissertations in this area of concentration

August 1996, Christopher Meek, Selecting Graphical Models: Causal and Statistical Modeling

August 1996,Thomas Richardson, Feedback Models: Interpretation and Discovery

August 1997, Oliver Schulte, Hard Choices in Scientific Inquiry


This sample curriculum is offered to illustrate how the core requirements of the program can be met by a student interested in Epistemology, Scientific Method, and Automated Discovery. Students are encouraged to design programs attuned to their own interests.


Fall First Year

Spring First Year

Fall Second Year

Spring Second Year

Fall Third Year

Spring Third Year