Category: Reinforcement Learning
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PPO vs A2C: CartPole Training Speed & Sample Efficiency
Compare PPO vs A2C on CartPole: which algorithm trains faster and uses samples more efficiently? Benchmark results reveal a clear winner.
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Gymnasium Custom Environment: 7 Patterns That Save Hours
Build Gymnasium custom environments faster with 7 proven patterns. Fix common pitfalls in reset(), step(), and observation spaces that waste hours.
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PPO vs DQN: Discrete Action Spaces Beat Continuous 3x
Compare PPO and DQN performance on discrete vs continuous control tasks. Surprising speed differences revealed through benchmark experiments.
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On-Policy vs Off-Policy RL: When PPO Beats SAC
PPO converges in 500K steps where SAC needs 2M โ but SAC wins on dense rewards. Real benchmarks, hyperparameter traps, and when to use which.
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RL Basics: MDP to Q-Learning in 5 Diagrams
Learn MDP fundamentals and Q-learning algorithms through 5 clear diagrams. Build intuition for reinforcement learning core concepts step-by-step.
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SAC Entropy Tuning: Auto-Alpha Cuts Failures by 80%
Learn SAC entropy tuning with auto-alpha to slash RL training failures by 80%. Discover the temperature coefficient trick that stabilizes learning.
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PPO vs SAC vs TD3: MuJoCo Humanoid Training in 5M Steps
Compare PPO, SAC, and TD3 on MuJoCo Humanoid: sample efficiency, stability, and final performance revealed in a 5M-step RL benchmark showdown.