TF-Agents implements core RL elements as modular Agents that define Policies for environment interaction and handle training from collected experience. It provides well-tested, scalable components for fast iteration on RL algorithms, supporting implementations like DQN, PPO, and various bandit strategies. The library integrates with TensorFlow for GPU-accelerated training and includes benchmarking and testing infrastructure.