Model-based reinforcement learning in TensorFlow
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Updated
Jul 27, 2021 - Python
Model-based reinforcement learning in TensorFlow
Study Model-Based Policy Optimization by varying the model estimator classes (e.g Decision Trees vs MLP)
Minimal model-based RL algorithm implementations
A reinforcement learning project exploring different RL algorithms. Namely: QLearning, DQN, PPO, TreeQN, SAVE,
UrbanWorldModel, UrbanSim WM is a DreamerV3-style world model for simulating city-scale air quality, energy, and mobility under policy interventions. It provides a Dockerized FastAPI + Next.js app with WAQI ETL integration, real-time PM2.5 inference, interactive charts, and a training pipeline in PyTorch.
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