Finding Theta

Lastest articles

Aligning and Augmenting Intelligence: A Technical Survey of Reinforcement Learning in Large Language Models

Learn how Reinforcement Learning from Human Feedback (RLHF) and emerging techniques like DPO are used to train safer, more helpful, and aligned Large Language Models (LLMs).

Mastering Autonomy: A Comprehensive Guide to the AutoDRIVE Ecosystem and Reinforcement Learning

A complete guide to the AutoDRIVE ecosystem. Learn to train self-driving car agents from scratch using reinforcement learning in this powerful Unity-based simulator.

Agentic AI: The Autonomous Evolution of Machine Learning and Its Dawn in Robotics

Explore Agentic AI, the next frontier in machine learning. Discover how autonomous agents learn, act independently, and are revolutionizing the field of robotics.

Serving Up Some Robotics: Setting Up a Tennis Environment in MuJoCo

Build a MuJoCo robot tennis simulation! Learn to set up a wall tennis environment, tackle physics/control challenges, understand its architecture, and improve it for robotics or reinforcement learning projects with MuJoCo

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

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

Beginner's Guide to Model-Based Reinforcement Learning (MBRL) with Atari's Breakout

Learn Model-Based Reinforcement Learning: Build sample-efficient RL agents by modeling environment dynamics and planning with Python in tasks like Atari's Breakout

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

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

Resolver las carreras de coches de Gymnasium con aprendizaje por refuerzo

Aprenda a aplicar el aprendizaje por refuerzo para resolver el juego Car Racing de Gymnasium, vea cómo funcionan los diferentes algoritmos y explore si los espacios de acción discretos o continuos son mejores.

Comparación del rendimiento de PPO, SAC y DQN en el Lunar Lander de Gymnasium

Explore cómo funcionan los diferentes algoritmos de aprendizaje por refuerzo dentro y fuera de la política en el Lunar Lander de Gymnasium

Michael Kudlaty

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August 1, 2024

Resolver el módulo de aterrizaje lunar de Gymnasium con Deep Q Learning (DQN)

Lastest articles

Aligning and Augmenting Intelligence: A Technical Survey of Reinforcement Learning in Large Language Models

Mastering Autonomy: A Comprehensive Guide to the AutoDRIVE Ecosystem and Reinforcement Learning

Agentic AI: The Autonomous Evolution of Machine Learning and Its Dawn in Robotics

Serving Up Some Robotics: Setting Up a Tennis Environment in MuJoCo

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

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

Beginner's Guide to Model-Based Reinforcement Learning (MBRL) with Atari's Breakout

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

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

Resolver las carreras de coches de Gymnasium con aprendizaje por refuerzo

Comparación del rendimiento de PPO, SAC y DQN en el Lunar Lander de Gymnasium