This Unity ML-Agents multi-agent training environment project integrates two distinct reinforcement learning scenarios—the roller agent navigation and a tank battle simulation—within a unified framework. By managing seeding, optimizing training configurations, ensuring device consistency, and effectively handling parallel environments, the project facilitates robust and scalable AI training across varied and complex scenarios.
- Unity 2022.3.39f1
- ML-Agents Release 21
- PyTorch 2.4.1 (+ CUDA 12.4)
- Python 3.10.12