COMP.4200 Artificial Intelligence (Formerly 91.420)
Id: 008104
Credits: 3-3
Description
Topics include: search techniques and their properties, including A*; game-playing, including adversarial and stochastic search; probabilistic reasoning, including Markov Decision Processes and Hidden Markov Models; and reinforcement learning, including value iteration and q-learning. Topics are developed theoretically and with programming assignments. The course includes a student-directed final project and paper.
Prerequisites
Co-req: COMP 3010 Organization of Programming Languages and MATH 3860 Probability and Statistics I.
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Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.