SOCIA-EVO: Automated Simulator Construction via Dual-Anchored Bi-Level Optimization

• URL: http://arxiv.org/abs/2604.17351v1
• Date: Sun, 19 Apr 2026 09:57:56 GMT
• Title: SOCIA-EVO: Automated Simulator Construction via Dual-Anchored Bi-Level Optimization
• Abstract summary: We propose SOCIA-EVO, a dual-anchored evolutionary framework for simulator construction.<n>By falsifying ineffective strategies through execution feedback, SOCIA-EVO achieves robust convergence, generating simulators that are statistically consistent with observational data.
• Score: 16.707429579441435
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Automated simulator construction requires distributional fidelity, distinguishing it from generic code generation. We identify two failure modes in long-horizon LLM agents: contextual drift and optimization instability arising from conflating structural and parametric errors. We propose SOCIA-EVO, a dual-anchored evolutionary framework. SOCIA-EVO introduces: (1) a static blueprint to enforce empirical constraints; (2) a bi-level optimization to decouple structural refinement from parameter calibration; and (3) a self-curating Strategy Playbook that manages remedial hypotheses via Bayesian-weighted retrieval. By falsifying ineffective strategies through execution feedback, SOCIA-EVO achieves robust convergence, generating simulators that are statistically consistent with observational data. The code and data of SOCIA-EVO are available here: https://github.com/cruiseresearchgroup/SOCIA/tree/evo.

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