Training High-Level Schedulers with Execution-Feedback Reinforcement Learning for Long-Horizon GUI Automation

Researchers developed CES, a multi-agent framework using reinforcement learning to improve GUI automation for long-horizon tasks. The system uses a Coordinator for planning, State Tracker for context management, and can integrate with any low-level Executor model to significantly enhance performance on complex automated tasks.