Quiz 2

BSDA5007

10 Internal Entities Declared
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198 - Multi-Armed Bandits- Exploration vs Exploitation
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199 - Markov Decision Processes & Bellman Equations
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200 - Dynamic Programming- Policy Evaluation, Value Iteration, and Policy Iteration
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201 - Monte Carlo Methods- First-Visit, Every-Visit, and Monte Carlo Control
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202 - Temporal Difference Learning- TD(0), TD(λ), and Eligibility Traces
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203 - Q-Learning and SARSA- Off-Policy and On-Policy TD Control
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204 - Deep Q-Networks- Experience Replay, Target Networks, Rainbow
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205 - Policy Gradients- REINFORCE and Actor-Critic
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206 - Actor-Critic Methods- A2C, A3C, and Advantage Estimation
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207 - Proximal Policy Optimization- Clipped Surrogate and Trust Regions
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Open library →Launch Assessment Engine