google-deepmind/scalable_agent

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1028 stars · 161 forks observed · 2026-08-28

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

A TensorFlow implementation of IMPALA (Importance Weighted Actor-Learner Architectures) for scalable distributed deep reinforcement learning, including a dynamic batching module. It supports single-machine and distributed training on DeepMind Lab environments such as DMLab-30.

Use cases

• train deep RL agents at scale with distributed actor-learner architecture
• reproduce IMPALA results on DMLab-30
• run reinforcement learning experiments on DeepMind Lab levels
• use importance-weighted V-trace off-policy correction
• dynamically batch experience from many parallel actors

When to choose

• you want a reference implementation of the IMPALA algorithm for research
• you need scalable distributed deep RL with many parallel environment actors
• you work with DeepMind Lab or similar environments in TensorFlow

When to avoid

• you need a maintained production library - the repo has not been updated since 2019
• you prefer PyTorch or modern RL frameworks
• you need official Google support or long-term compatibility with recent TensorFlow versions

Facets

library · maturity maintenance

machine-learning reinforcement-learning deep-learning streaming reinforcement-learning machine-learning deep-learning python impala actor-learner tensorflow deepmind-lab distributed-training research-code linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-deepmind/scalable_agent")