Simulation technologies have been widely utilized in many scientific research fields such as weather forecasting, fluid mechanics and biological populations. It is the best tool to handle problems in complex systems, where closed-form expressions are unavailable and the target distribution in the representation space is too complex to be fully represented by a deep learning (DL) model. We believe that the development of simulation technologies is consistent with scientific paradigms. This paper induces the evolution of scientific paradigms from the perspective of data, algorithms, and computational power. Building upon this perspective, we divide simulation technologies into three stages aligning with the emergence of new paradigms, and find that advanced simulation technologies are typical instances of paradigms integration. Moreover, we propose the concept of behavioral simulation (BS), specifically sophisticated behavioral simulation (SBS), representing a higher degree of paradigms integration based on foundation models to simulate complex social systems involving sophisticated human strategies and behaviors. BS and further SBS are designed to tackle challenges concerning the complex human system that surpasses the capacity of traditional agent-based modeling simulation (ABMS), which can be regarded as a possible next paradigm for science. Through this work, we look forward to more powerful BS and SBS applications in scientific research branches within social science.

翻译：模拟技术已广泛应用于天气预报、流体力学和生物种群等众多科学研究领域。它是处理复杂系统问题的最佳工具，此类系统中不存在封闭形式的解析表达式，且表示空间中的目标分布过于复杂，无法由深度学习模型完全表征。我们认为，模拟技术的发展与科学范式的演进相一致。本文从数据、算法和算力视角出发，推演了科学范式的演变过程。基于这一视角，我们将模拟技术划分为与新兴范式出现相对应的三个阶段，并发现先进模拟技术是范式整合的典型实例。此外，我们提出了行为模拟（BS）的概念，特别是精细化行为模拟（SBS），它代表了基于基础模型实现的更高程度范式整合，用于模拟涉及人类复杂策略与行为的复杂社会系统。BS以及更进一步的SBS旨在应对超越传统基于智能体的建模与模拟（ABMS）能力的复杂人类系统挑战，可被视为科学的可能下一个范式。通过本研究，我们期待在社会科学科研分支中涌现更强大的BS与SBS应用。