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Welcome to the 2020 Edition of 6.034
6.034 introduces representations, methods, and architectures used to build applications and to account for human intelligence from a computational point of view. It covers applications of rule chaining, constraint propagation, constrained search, inheritance, statistical inference, and other problem-solving paradigms. It also addresses applications of identification trees, neural nets, genetic algorithms, support-vector machines, boosting, and other machine learning paradigms. Class work includes programming assignments, quizzes, and written assignments related to some of the lectures.
6.844 was created in response to requests from grad students who wanted to take 6.034, but needed graduate level credit. It is a supplement to 6.034---students take 6.034, and in addition attend a weekly 6.844 session. For each 6.844 session, students read an assigned paper or papers from the research literature, write up a one page response to a set of provided questions, and come to class prepared to discuss your (and others') answers to those questions. To keep the class size manageable and to encourage active class participation, we do not allow listeners.
More details about 6.034 and 6.844 will be coming soon....
