Probabilistic Decision Making
Lecture, three hours; discussion, one hour. Requisite: course 100A. Recommended preparation: experience with Python. Formulation of decision making problem as probabilistic inference. Derivation algorithms for solving probabilistic decision making. Implementation of code that executes inference and decision. Covers Markov decision process, planning, search, and reinforcement learning. Letter grading.
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Enrollment Progress
Jul 9, 4 PM PDT
LEC 1: 70/70 seats taken (Full)
Section List
LEC 1
ClosedMW 11am-12:15pm
Geology Building 4660