Finding Theta

Lastest articles

The Evolution of Imagination: A Deep Dive into DreamerV3 and its Conquest of Minecraft

Explore DreamerV3, the AI that taught itself to find diamonds in Minecraft, revolutionizing reinforcement learning with its powerful world model.

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).

The Unseen Hand: Guiding a Virtual Drone with Sparse and Dense Rewards

Exploring training a drone with reinforcement learning, focusing on the trade-offs between sparse and dense rewards to achieve agile flight while avoiding unintended "reward hacking."

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

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.

Michael Kudlaty

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February 1, 2025

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

Lastest articles

Tennis Part 2

F1Tenth

Dreamer V4

Picar

Reinforce Tactics

Mujoco Playground

The Evolution of Imagination: A Deep Dive into DreamerV3 and its Conquest of Minecraft

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

The Unseen Hand: Guiding a Virtual Drone with Sparse and Dense Rewards

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

Using Reinforcement Learning for Stock Trading with FinRL