arXiv — cs.AI preprintsInternational9 October 2026
The Red Queen G\"odel Machine: Co-Evolving Agents and Their Evaluators
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arXiv:2606.26294v3 Announce Type: replace-cross Abstract: Self-improving agents are state-of-the-art on agentic coding benchmarks, yet their search methods assume a stationary evaluation criterion. This ignores a central feature of evolution: species adapt as their environments change with them. We introduce the Red Queen G\"odel Machine (RQGM), an evolutionary framework for recursive self-improvement under non-stationary utilities. This allows learned evaluators to improve alongside the agents they guide. On DeepSWE, the RQGM improves over its fixed-evaluator baseline by adding a complementar
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