Intelligent Agents and Search Algorithms
About this course
Intelligent Agents and Search Algorithms is your gateway to understanding how machines make decisions, solve problems, and act rationally in complex environments. In this course, you’ll explore the foundational principles that power intelligent systems—starting with agent architectures and environment types, and progressing into the design of goal-driven, rational behavior. You’ll examine how search enables AI systems to navigate uncertainty and make optimal choices, diving into uninformed and informed strategies such as breadth-first search, depth-first search, A*, and adversarial search. You’ll also learn how heuristics shape efficiency and performance—an essential concept for building scalable, high-performing AI systems. More than a theoretical overview, this course emphasizes applied skill-building. Through hands-on programming assignments and algorithm analysis, you’ll compare performance trade-offs, implement search strategies, and evaluate real-world problem-solving approaches. As part of CU Boulder’s MS in Artificial Intelligence, this course equips you with the conceptual clarity and technical foundation required for AI development, systems design, and advanced study. Whether you’re preparing to build intelligent systems or elevate your role in an AI-driven organization, mastering agents and search is a critical step forward in your career.
83/100
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- 32/45
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- 35/35
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- 16/20
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What you'll learn
- understand agent architectures
- identify different types of environments
- design goal-driven rational behavior
- implement breadth-first search, depth-first search, A*, and adversarial search
- analyze the impact of heuristics on algorithm efficiency
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