Reinforcement Learning Projects
Explore real-world RL applications, from autonomous systems to game strategies.
🎯 Start ExperimentingFeatured Reinforcement Learning Projects
Self-Driving Car Controller
A project exploring deep reinforcement learning for autonomous navigation tasks and safety optimization.
Game AI Agent Development
Design AI agents for games using Q-learning and policy gradients, with benchmarks on popular environments like CartPole.
Resource Management Optimization
Apply RL techniques to problems like energy grid balancing and inventory control with simulated reward models.
Explore Categories
Q-Learning Fundamentals
Learn the basics of tabular RL methods through grid world and simple decision problems.
Deep Q-Networks (DQN)
Implement advanced RL with neural networks on complex environments like OpenAI Gym MuJoCo.
Policy Gradients
Train policy gradient agents for continuous action spaces and policy optimization techniques.
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