AI RESEARCH
EPOCH: An Agentic Protocol for Multi-Round System Optimization
arXiv CS.AI
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ArXi:2603.09049v1 Announce Type: new Autonomous agents are increasingly used to improve prompts, code, and machine learning systems through iterative execution and feedback. Yet existing approaches are usually designed as task-specific optimization loops rather than as a unified protocol for establishing baselines and managing tracked multi-round self-improvement. We