Tema
5 artículos
Using reinforcement learning (RL), specifically Truncated Quantile Critics (TQC) and Deep Deterministic Policy Gradient (DDPG), to solve the Fetch environments in Gymnasium Robotics
Leer artículo
Train an RL agent to master Atari's Pong with sparse rewards and high-dimensional inputs. Explore preprocessing, replay buffers, and performance-boosting strategies
Leer artículo
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.
Leer artículo
Explore how different On-Policy and Off-Policy reinforcement learning algorithms perform on Gymnasium's Lunar Lander
Leer artículo
Aprende cómo funciona el algoritmo de aprendizaje por refuerzo Deep Q-Learning (DQN) y aplícalo para resolver Lunar Lander de Gymnasium.
Leer artículo