EPOCH: An Agentic Protocol for Multi-Round System Optimization
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 introduce EPOCH, an engineering protocol for multi-round system optimization in heterogeneous environments. EPOCH organizes optimization into two phases: baseline construction and iterative self-improvement. It further structures each round through role-constrained stages that separate planning, implementation, and evaluation, and standardizes execution through ...
| Authors | Zhanlin Liu, Yitao Li, Munirathnam Srikanth |
|---|---|
| Primary category | cs.AI |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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