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From Zero to Dino-Roar: Teaching a T-Rex to Walk with MuJoCo and Reinforcement Learning

Build a bipedal T-Rex model in MuJoCo and lay the groundwork for teaching it to walk using reinforcement learning techniques like PPO or SAC. Get the XML, Python setup, and conceptual RL overview

Mastering Atari's Pong with Reinforcement Learning: Overcoming Sparse Rewards and Optimizing Performance

Train an RL agent to master Atari's Pong with sparse rewards and high-dimensional inputs. Explore preprocessing, replay buffers, and performance-boosting strategies

Bridging Worlds: How Visual Language Action Models are Teaching Robots to See, Understand, and Act

Understand how Visual Language Action Models (VLAs) let robots follow commands by fusing AI vision and language for action, demonstrated with a conceptual Python robotics simulation

Using Multi-Agent Reinforcement Learning to play OpenSpiel's Connect 4 with Ray's RLlib

Discover how self-play can be used to train a reinforcement learning agent to master Connect 4, achieving advanced strategies without human intervention

Using Reinforcement Learning for Stock Trading with FinRL

Learn stock trading with Reinforcement Learning (RL) and FinRL. This guide covers RL theory, FinRL setup, agent training (DQN, PPO), backtesting, and practical considerations, including code examples and pitfalls.

Solving Gymnasium's Car Racing with Reinforcement Learning

Learn how to apply reinforcement learning to solve Gymnasium's Car Racing game, see how different algorithms perform, and explore whether discrete or continuous action spaces are better.

Michael Kudlaty

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September 1, 2024