15-281 Artificial Intelligence: Representation and Problem Solving
12 units, Carnegie Mellon University
This course is about the theory and practice of Artificial Intelligence. We will study modern techniques for computers to represent task-relevant information and make intelligent (i.e. satisficing or optimal) decisions towards the achievement of goals. The search and problem solving methods are applicable throughout a large range of industrial, civil, medical, financial, robotic, and information systems. We will investigate questions about AI systems such as: how to represent knowledge, how to effectively generate appropriate sequences of actions and how to search among alternatives to find optimal or near-optimal solutions. We will also explore how to deal with uncertainty in the world, how to learn from experience, and how to learn decision rules from data. ***Starting Spring 2026, most students should enroll in 07-280 rather than 15-281. Enrollment in 15-281 is by special permission only, for students who have already completed 10-315 (or a similar ML course) and specifically need 10-315 + 15-281 to complete a degree requirement.***
Prerequisites: 15-122 (min C) and (18-202 (min C) or 21-241 (min C) or 21-240 (min C) or 21-254 (min C)) and (21-127 (min C) or 21-128 (min C) or 15-151 (min C))
Offered: Spring 2026, Fall 2025
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