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The Deadly Triad in Reinforcement Learning: Why Agents Fail and How DQN Fixed It
A deep dive into function approximation, bootstrapping, and off-policy learning.
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A Deep Dive into Q-Learning: The Off-Policy TD Control Algorithm
How Q-Learning Works: From Off-Policy Foundations to Update Rules, SARSA Comparison, and Real-World Insights
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A Deep Dive into On-Policy TD Control: The SARSA Algorithm
How on-policy learning makes agents cautious by design.
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Temporal Difference: Bootstrapping in Reinforcement Learning
Understanding differences between TD Learning and MC Learning in RL
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Monte Carlo Learning in RL
Understanding the role of full episode returns, discount factors, and the no-bootstrapping principle in RL.