tensorflow/agents

Health v2 · maintenance only

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3025 stars · 752 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TF-Agents is a TensorFlow-based Python library for building, training, and deploying reinforcement learning and contextual bandit algorithms. It provides well-tested modular components such as agents, policies, and replay buffers, along with implementations of algorithms like DQN, DDPG, TD3, PPO, SAC, and REINFORCE.

Use cases

• train a DQN agent on Cartpole
• implement a custom reinforcement learning algorithm in TensorFlow
• solve contextual bandit problems
• prototype and benchmark RL algorithms
• train a soft actor-critic agent for continuous control
• learn reinforcement learning through tutorials

When to choose

• you want reliable, modular, well-tested RL components in TensorFlow
• you need standard algorithms like DQN, PPO, or SAC out of the box
• you are working on contextual bandits or multi-armed bandits
• you want fast iteration with good test integration and benchmarking

When to avoid

• you prefer PyTorch over TensorFlow
• you need a fully stable API with no breaking changes
• you only need lightweight RL without deep learning frameworks

Facets

library · maturity active

machine-learning reinforcement-learning benchmarking sdk reinforcement-learning machine-learning deep-learning python tensorflow reinforcement-learning contextual-bandits multi-armed-bandits dqn ppo sac rl-algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="tensorflow/agents")