CS 234 Reinforcement Learning

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The CS 234 Reinforcement Learning course module will offer a solid introduction to the area of reinforcement learning and students will explore about the core challenges and approaches, comprising the generalization and exploration.

By the end of the class students will be competent to:

• State the main characteristics of reinforcement learning that differentiates it from AI and non-interactive machine learning.
• Apply in code common RL algorithms.
• Explain (list and define) numerous criteria for examining the RL algorithms and assess algorithms on these metrics, example: regret, sample complexity, computational complexity, convergence, empirical performance, and so on.
• Explain the exploration vs. exploitation challenge and compare as a minimum of two approaches for addressing this challenge.

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