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Computational Modeling

16:198:504

Note: This course may not be taken for credit toward the MS and Ph.D. degrees in computer science.  It is primarily intended for cognitive science students who do not have undergraduate degrees in computer science.

This course offers a hands-on introduction to computational modeling as a methodology for explaining the behavior of complex and intelligent systems. The course aims for a broad audience of graduate students who need to master computational ideas and tools for their research practice.

Credits: 
3
Topics: 

Generative models, statistical models, nondeterministic models, rule-based systems, and knowledge-based modeling techniques. Case studies in the analysis of perception and action.

Expected Work: 

In-class exercises, interactive recitations conducted in a computer laboratory, and weekly homeworks. Grades will be assigned based on homeworks, class participation, and take-home midterm and final exams.

Professor: 
Matthew Stone
Semester: 
Fall
Course Type: 
Graduate

Check the University Schedule of Classes to see if this course is open.

Request a Special Permission Number here if the class is full.