facebookresearch/ELF

Health v2 · maintenance only

Flags: no_releases archived no_license

Adoption not part of the score

2090 stars · 281 forks observed · 2026-08-28

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

ELF is an end-to-end, lightweight and flexible C++/Python platform for game research, focused on real-time strategy games. It hosts multiple game instances concurrently in C++, exposes batched game states to Python, and ships with a fast RTS engine, MiniRTS, Capture the Flag, Tower Defense, and a PyTorch-based reinforcement learning backend.

Use cases

• train RL agents to play real-time strategy games
• run thousands of concurrent game environments for reinforcement learning
• research self-play and multi-agent RL algorithms
• build custom RTS-like game environments with full access to game internals
• benchmark RL algorithms on miniature RTS games like MiniRTS
• plug existing C/C++ games into an RL training pipeline

When to choose

• you need high-throughput concurrent game simulation for RL research
• you want a fast, lightweight RTS environment with modifiable game dynamics
• you are studying self-play, MCTS, or batched actor-learner RL algorithms

When to avoid

• you need a maintained project with recent updates and active support
• you want turn-based or 3D game environments rather than RTS-style games
• you need a simple single-environment Gym-style interface without concurrency

Facets

framework · maturity maintenance

reinforcement-learning simulation game-engine machine-learning deep-learning reinforcement-learning artificial-intelligence machine-learning cpp python cross-platform rts-games game-research rl-environments concurrent-simulation self-play pytorch facebook-research game-development linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="facebookresearch/ELF")