Category: Reinforcement Learning
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DQN Overestimation Bias: 3 Double-Q Fixes That Work
DQN agents plateau at 60% optimal? Overestimation bias is why. Compare 3 Double-Q fixes on LunarLander with real training curves.
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PPO Training Diverges After 1M Steps: Clipping & LR Fixes
PPO training collapse after 1M steps? Learn how gradient clipping and learning rate schedules prevent policy divergence in deep RL implementations.
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PPO vs SAC: Real Robot Benchmark on 3 Manipulation Tasks
Compare PPO vs SAC on real robot manipulation tasks. Performance metrics, training stability, and practical deployment insights revealed.
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Gymnasium vs Stable Baselines3 vs RLlib: API Complexity
Beginners waste weeks on RLlib setup before training one agent. Here's why Stable Baselines3 beats distributed frameworks for your first 3 RL projects.
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DQN vs PPO vs SAC: MuJoCo Training Speed Benchmarks
DQN fails on continuous control. SAC beats PPO 2-3x in sample efficiency but costs 20% more wall-clock time. Real benchmarks on HalfCheetah, Hopper, Ant.
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Custom Gymnasium Environment: Portfolio Project Guide
Build a custom Gymnasium environment from scratch for your portfolio. Learn registration, spaces, and reward shaping that makes recruiters take notice.
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DreamerV3 World Model RL: 200-Line PyTorch Implementation
Build DreamerV3's world model RL from scratch in 200 lines โ RSSM dynamics, latent-space dreaming, and KL balancing tricks that prevent collapse.
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SimpleRL: Building DQN to PPO from Scratch in 500 Lines
Build DQN and PPO reinforcement learning algorithms from scratch in under 500 lines. Step-by-step implementation guide with minimal dependencies.