War Workload Aware Rollouts For Synchronous Agenti

# WAR: Workload-Aware Rollouts for Synchronous Agentic Reinforcement Learning

Derived from arXiv:2607.17299 - WAR: Workload-Aware Rollouts for Synchronous Agentic Reinforcement Learning

## Core Concept
Long-horizon rollout generation has become the dominant systems bottleneck in agentic reinforcement learning (RL). As agents interact with environments over many turns, trajectories rapidly grow to tens of thousands of tokens, making synchronous RL training increasingly constrained by rollout. We propose WAR, a workload-aware rollout system that substantially accelerates synchronous agentic RL by jointly optimizing decoding and scheduling. WAR is built on a key observation: the optimal rollout o...

## Key Insights
- Derived from arXiv:2607.17299
- Published: 2026-07-19
- Utility Score: 1.00
- Authors: Ryan Xu, Atlas Zhao, David Bao et al.

## Activation
war-workload-aware-rollouts-for-synchronous-agenti, 2607.17299

## References
- arXiv: https://arxiv.org/abs/2607.17299