nortem/marl-gpt-datasets
收藏Hugging Face2026-03-02 更新2026-03-29 收录
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资源简介：
---
license: mit
pretty_name: MARL-GPT Datasets
tags:
- reinforcement-learning
- multi-agent
- offline-rl
- trajectories
task_categories:
- reinforcement-learning
---
# MARL-GPT Datasets
Offline expert trajectories from **“MARL-GPT: Foundation Model for Multi-Agent Reinforcement Learning”**.
## Environments
This dataset includes trajectories from the three evaluation domains used in MARL-GPT: **SMACv2** (StarCraft multi-agent combat), **Google Research Football (GRF)**, and **POGEMA** (partially observable multi-agent pathfinding on grids).
## Format
Trajectories are stored sequentially (no shuffling). Use the `done` flag to split the stream into per-agent trajectory segments.
Each transition is:
- `(obs, act, rew, done)`
Training-ready data is provided as a flattened dict of tensors:
- `obs`: `(B, n_obs_feat)`
- `act`: `(B,)`
- `rew`: `(B,)`
- `done`: `(B,)` (optional)
- `info_battle_won`: `(B,)` (optional)
- `action_mask`: `(B, n_act)` (optional)
`B` is the number of transitions in the flattened stream.
提供机构：
nortem
