GitHub - agentsea/r1-computer-use: Applying the ideas of Deepseek R1 to computer use

An experimental project applying large-scale Reinforcement Learning techniques to computer usage scenarios, utilizing neural reward models to validate agent actions. The system implements a three-step cycle extending ReACT into reinforcement learning, with multiple training stages focused on developing reasoning skills for computer interaction.

Deep Reinforcement Learning: Pong from Pixels

A comprehensive exploration of Reinforcement Learning (RL) through implementing a Pong-playing AI using Policy Gradients, demonstrating how neural networks can learn complex behaviors from raw pixel inputs with minimal preprocessing and assumptions.