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CS 321 Making Decisions with Artificial Intelligence 6 credits
There are many situations where computer systems must make intelligent choices, from selecting actions in a game, to suggesting ways to distribute scarce resources for monitoring endangered species, to a search-and-rescue robot learning to interact with its environment. Artificial intelligence offers multiple frameworks for solving these problems. While popular media attention has often emphasized supervised machine learning, this course instead engages with a variety of other approaches in artificial intelligence, both established and cutting edge. These include intelligent search strategies, game playing approaches, constrained decision making, reinforcement learning from experience, and more. Coursework includes problem solving and programming.
- Winter 2027
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 or MATH 236 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 321.01 Winter 2027
- Faculty: Chelsey Edge 🏫 👤
- Size:28
- M, WHulings 316 1:50pm-3:00pm
- FHulings 316 2:20pm-3:20pm
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x Seats held for CS Match until the day after X priority registration.