SHING CIVITAS一场关于人工文明的开放实验
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附录 C·v3.0

SHING CIVITAS — 参考文献核验登记（v3）

本系列引用的全部外部文献，已于 2026-11-12 对照出版社、DOI 与图书馆记录核验。

发布日期 3 分钟阅读中文版 · English

2026-11-12 对照出版社、DOI、正式会议论文集及图书馆目录核验；书目信息核对不等于外部文献复核或认可 SHING CIVITAS 实验结论。

已核对条目

  1. Schelling, T. C. (1971). Dynamic models of segregation. The Journal of Mathematical Sociology, 1(2), 143–186. https://doi.org/10.1080/0022250X.1971.9989794
  2. Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Brookings Institution Press / MIT Press. https://www.brookings.edu/books/growing-artificial-societies/
  3. Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. https://press.princeton.edu/books/paperback/9780691015675/the-complexity-of-cooperation
  4. Epstein, J. M. (2008). Why model? Journal of Artificial Societies and Social Simulation, 11(4), 12. https://www.jasss.org/11/4/12.html
  5. Park, J. S., O’Brien, J. C., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023). Generative agents: Interactive simulacra of human behavior. Proceedings of UIST ’23, Article 2, 1–22. https://doi.org/10.1145/3586183.3606763
  6. Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024). Cooperate or collapse: Emergence of sustainable cooperation in a society of LLM agents. Advances in Neural Information Processing Systems 37 (NeurIPS 2024). https://proceedings.neurips.cc/paper_files/paper/2024/hash/ca9567d8ef6b2ea2da0d7eed57b933ee-Abstract-Conference.html
  7. Ashery, A. F., Aiello, L. M., & Baronchelli, A. (2025). Emergent social conventions and collective bias in LLM populations. Science Advances, 11(20), eadu9368. https://doi.org/10.1126/sciadv.adu9368
  8. Horton, J. J., Filippas, A., & Manning, B. S. (2023; revised 2026). Large language models as simulated economic agents: What can we learn from Homo silicus? NBER Working Paper No. 31122. https://doi.org/10.3386/w31122
  9. Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118. https://doi.org/10.2307/1884852
  10. Law, A. M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill. https://www.mheducation.com/highered/product/simulation-modeling-and-analysis-law
  11. Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1–26. https://doi.org/10.1214/aos/1176344552
  12. Dixon, W. J., & Mood, A. M. (1946). The statistical sign test. Journal of the American Statistical Association, 41(236), 557–566. https://doi.org/10.1080/01621459.1946.10501898
  13. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6(2), 65–70. https://www.jstor.org/stable/4615733
  14. Matheson, J. E., & Winkler, R. L. (1976). Scoring rules for continuous probability distributions. Management Science, 22(10), 1087–1096. https://doi.org/10.1287/mnsc.22.10.1087
  15. Gneiting, T., & Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102(477), 359–378. https://doi.org/10.1198/016214506000001437
  16. Windrum, P., Fagiolo, G., & Moneta, A. (2007). Empirical validation of agent-based models: Alternatives and prospects. Journal of Artificial Societies and Social Simulation, 10(2), 8. https://www.jasss.org/10/2/8.html
  17. Grimm, V., Railsback, S. F., Vincenot, C. E., et al. (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23(2), 7. https://doi.org/10.18564/jasss.4259
  18. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/S0140525X0999152X
  19. Axelrod, R. (1984). The Evolution of Cooperation. Basic Books. https://search.worldcat.org/title/The-evolution-of-cooperation/oclc/10274775
  20. Hamilton, W. D. (1964). The genetical evolution of social behaviour. I & II. Journal of Theoretical Biology, 7(1), 1–16 and 17–52. https://doi.org/10.1016/0022-5193(64)90038-4 ; https://doi.org/10.1016/0022-5193(64)90039-6
  21. Nowak, M. A., & Sigmund, K. (1998). Evolution of indirect reciprocity by image scoring. Nature, 393, 573–577. https://doi.org/10.1038/31225
  22. Böhm-Bawerk, E. von (1889). Positive Theorie des Kapitales [The Positive Theory of Capital, English translation by W. Smart, 1891]. Original German work (1889); 1891 edition: https://books.google.com/books?id=aGvFdurcBSwC
  23. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press. https://mitpress.mit.edu/9780262039246/reinforcement-learning/
  24. DeepSeek. (2026, October 17). DeepSeek-V4.1-Flash-1017 model update (API alias deepseek-flash). DeepSeek API change log. https://api-docs.deepseek.com/updates/
  25. Särkkä, S. (2013). Bayesian Filtering and Smoothing. Cambridge University Press. https://doi.org/10.1017/CBO9781139344203

更正与说明

  • Horton： NBER 工作论文 31122 实为 Horton、Filippas 和 Manning 三位作者，2023 年首发、2026 年 2 月修订；v2 只写一位作者属著录不全。
  • Hamilton： 《The genetical evolution of social behaviour》分为上、下两篇，I 为 1–16 页，II 为 17–52 页，各有独立 DOI；v2 未区分页码。
  • Grimm 等： 正文用 et al. 缩写作者，期刊原文提供完整作者名单。
  • Böhm-Bawerk： 已区分 1889 年德文原著和 1891 年英译本，并未混为同一版本。
  • Särkkä： 剑桥出版社同时列出多种介质版本和日期；本书引用的 2013 年版本有出版记录支持。
  • DeepSeek 模型： 2026-10-17 官方公告指出 deepseek-flash 已切至 DeepSeek-V4.1-Flash-1017；P19 于 2026-11-06 运行，但未存档不可变快照号，因此具体路由版本的说明基于公告与日期推定。

正文原编号保留；仅 P19 新增 [6]，引用模型提供方公告。外部文献仅用于背景与方法，SHING CIVITAS 数值结果仍以实验数据为依据。