Use Cases

Real-world applications

Training Reinforcement Learning Agents

Developers and researchers can train RL agents on standard benchmarks like Atari or PyBullet using PyTorch implementations.

Algorithm Benchmarking and Comparison

Users can benchmark different RL algorithms under a unified interface to evaluate performance on custom or standard environments.