195M steps of 10-agent CS:GO state → action data (with damage labels), free for research
If you work on imitation learning or multi-agent behaviour: we just released 9,515 bot-played CS:GO matches. Per 16 Hz step for each of ten agents: actions (buttons + mouse), state (pose, health, weapon…) and who-hit-whom damage. 218,768 rounds, ≈3,958 h of play. 14% of the matches also have the ten first-person videos, aligned frame by frame.
Expert bots on one map with pistols, so it is a clean, narrow testbed rather than human play. Parquet + webdataset videos, CC BY-NC 4.0: https://huggingface.co/datasets/v0rt3ch/cs-5v5-bots-aim\_usp-3k · spec and a round you can watch from all ten POVs: https://vor.tech/?utm\_source=reddit&utm\_medium=social&utm\_campaign=launch-2026-10&utm\_content=r-reinforcementlearning
u/bengal7ion — 12 days ago