Environment Scaling Emerges as Biggest Challenge in Agentic RL

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Another point to consider that drives home the importance / complexity of environment management:

If we assume one environment per rollout in RL, we can have O(100) environments running concurrently for each policy update (assuming only one RL run at a time). But, frontier evals today often use multiple containers per task. For example, each task in Cybench has:

1. A single container for terminal commands. 2. One or more separate Docker containers hosting remote task servers.

These containers are connected via a shared Docker network. The number of concurrent containers can easily reach O(1K) if we RL train on similar setups. And, Evals / envs will become more realistic over time as well, leading to more complex Docker networks!

Cameron R. Wolfe, Ph.D.@cwolferesearch

One of the hardest aspects of agentic RL is managing / scaling environments...

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