Datasets › SMAC
SMAC (The StarCraft Multi-Agent Challenge)
The StarCraft Multi-Agent Challenge (SMAC) is a benchmark that provides elements of partial observability, challenging dynamics, and high-dimensional observation spaces. SMAC is built using the StarCraft II game engine, creating a testbed for research in cooperative MARL where each game unit is an independent RL agent.
Benchmarks archive 2025-07-28
All 5 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| SMAC | SMAC 6h_vs_8z | ACE Median Win Rate 93.75 | ACE: Cooperative Multi-agent Q-learning with... | opendilab/ace | 14 | Compare |
| SMAC | SMAC MMM2 | ACE Median Win Rate 100 | ACE: Cooperative Multi-agent Q-learning with... | opendilab/ace | 14 | Compare |
| SMAC | SMAC 3s5z_vs_3s6z | ACE Median Win Rate 100 | ACE: Cooperative Multi-agent Q-learning with... | opendilab/ace | 13 | Compare |
| SMAC | SMAC corridor | ACE Median Win Rate 100 | ACE: Cooperative Multi-agent Q-learning with... | opendilab/ace | 13 | Compare |
| SMAC | SMAC 27m_vs_30m | DDN Median Win Rate 91.48 | DFAC Framework: Factorizing the Value Function via... | j3soon/dfac | 11 | Compare |
Papers archive 2025-07-28
5 shown of 5 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 324. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning | 1 | 10 | 4 Jun 2023 | not harvested |
| ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency | 1 | 4 | 29 Nov 2022 | ran 0 of 4 samples (4 unverified) |
| DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning | 1 | 30 | 16 Feb 2021 | ran 1 of 1 samples (0 unverified) |
| Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning | 1 | 5 | 19 Mar 2020 | ran 1 of 1 samples (0 unverified) |
| The StarCraft Multi-Agent Challenge | 23 | 16 | 11 Feb 2019 | ran 6 of 15 samples (9 unverified; 13 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- SMAC MMM2
- SMAC 6h_vs_8z
- SMAC 3s5z_vs_3s6z
- SMAC corridor
- SMAC 27m_vs_30m
- SMAC
6 variant names, as the archive lists them.
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