nithisha2201

One thing missing from most RL environment discussions is observability during training. Single-agent envs are hard enough to debug, but multi-agent environments are a completely different challenge, reward curves tell you almost nothing about which agent failed or why cooperation broke down.

Interesting, how do you handle the observability side during training? One thing I ran into with multi-agent RL is that reward signals alone don't tell you much about why an agent is failing. Curious if you've built any tooling around that.