Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Social Simulation for Non-hackers

  • Conference paper
  • First Online:
Multi-Agent-Based Simulation XXII (MABS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13128))

Abstract

Computer simulation is a powerful tool for social scientists, but popular platforms require representing the semantics of the model being simulated in computer code, leading to models that are either expensive to construct, inefficient, or inaccurate. We introduce SCAMP (Social Causality using Agents with Multiple Perspectives), a social simulator that uses stigmergy to execute models that are written as concept maps and spreadsheets, without requiring any programming expertise on the part of the modeler. This Repast-based framework has been extensively exercised in the DARPA Ground Truth program to generate realistic social data for analysis by social scientists.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    In addition to the author, the SCAMP team included J.A. Morell of 4.699 LLC; L. Sappelsa of ANSER LLC; J. Greanya and S. Nadella of Wright State Research Institute (now Parallax Advanced Research). Kathleen Carley of CMU consulted on social network issues.

References

Papers by the author are available at https://www.abcresearch.org/abc/papers

  1. Argonne National Laboratory: Repast Agent Simulation Toolkit. Argonne National Laboratory (2007). http://repast.sourceforge.net/

  2. Busemeyer, J.R., Townsend, J.T.: Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. Psychol. Rev. 100(3), 432–459 (1993)

    Article  Google Scholar 

  3. Cioffi-Revilla, C.: Introduction to Computational Social Science, 2nd edn. Springer, Cham (2017). https://doi.org/10.1007/978-1-4471-5661-1

    Book  MATH  Google Scholar 

  4. Crossman, J., Bechtel, R., Parunak, H.V.D., Brueckner, S.: Integrating dynamic social networks and spatio-temporal models for risk assessment, wargaming and planning. The Network Science Workshop, West Point, NY (2009)

    Google Scholar 

  5. de Marchi, S.: Computational and Mathematical Modeling in the Social Sciences. Cambridge University Press, Cambridge (2005)

    Book  Google Scholar 

  6. Epstein, J.M.: Generative Social Science. Princeton University Press, Princeton (2006)

    MATH  Google Scholar 

  7. Gilbert, N., Troitzsch, K.G.: Simulation for the Social Scientist, 2nd edn. Open University Press, Buckingham (2005)

    Google Scholar 

  8. Grassé, P.-P.: La reconstruction du nid et les coordinations interindividuelles chezBellicositermes natalensis etCubitermes sp. la théorie de la stigmergie: Essai d’interprétation du comportement des termites constructeurs. Ins. Soc. 6, 41–84 (1959). https://doi.org/10.1007/BF02223791

    Article  Google Scholar 

  9. Heuer, R.J., Jr., Pherson, R.H.: Structured Analytic Techniques for Intelligence Analysis. CQ Press, Washington, DC (2010)

    Google Scholar 

  10. Horling, B., et al.: The TÆMS White Paper. Multi-Agent Systems Lab, University of Massachusetts, Amherst (2004). http://mas.cs.umass.edu/pub/paper_detail.php/182

  11. IHMC: IHMC CmapTools – Download, Pensacola, FL (2013). https://cmap.ihmc.us/cmaptools/

  12. Kahneman, D., Tversky, A.: The simulation heuristic. In: Kahneman, D., Slovic, P., Tversky, A. (eds.) Judgment Under Uncertainty: Heuristics and Biases, pp. 201–208. Cambridge University Press, Cambridge (1982)

    Chapter  Google Scholar 

  13. Klein, G.A.: Sources of Power: How People Make Decisions. MIT Press, Cambridge (1998)

    Google Scholar 

  14. Lindley, C.A.: Story and narrative structures in computer games. In: Bushoff, B. (ed.) Developing Interactive Narrative Content. High Text Verlag, München (2005)

    Google Scholar 

  15. Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: MASON: a multiagent simulation environment. Simulation 81, 517–527 (2005)

    Article  Google Scholar 

  16. Mosteller, F., Nogee, P.: An experimental measurement of utility. J. Polit. Econ. 59, 371–404 (1951)

    Article  Google Scholar 

  17. Parunak, H.V.D.: A survey of environments and mechanisms for human-human stigmergy. In: Weyns, D., Parunak, H.V.D., Michel, F. (eds.) E4MAS 2005. LNCS (LNAI), vol. 3830, pp. 163–186. Springer, Heidelberg (2006). https://doi.org/10.1007/11678809_10

  18. Parunak, H.V.D.: Real-time agent characterization and prediction. In: International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2007), Industrial Track, Honolulu, Hawaii, pp. 1421–1428, ACM (2007)

    Google Scholar 

  19. Parunak, H.V.D.: Psychology from stigmergy. In: Computational Social Science (CSS 2020), vol. (forthcoming). CSSSA, Santa Fe (2020)

    Google Scholar 

  20. Parunak, H.V.D., et al.: Stigmergic modeling of hierarchical task networks. In: Gennaro Tosto, H., Parunak, D. (eds.) MABS 2009. LNCS (LNAI), vol. 5683, pp. 98–109. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13553-8_9

  21. Parunak, H.V.D., Bisson, R., Brueckner, S.A.: Agent interaction, multiple perspectives, and swarming simulation. In: Proceedings of the International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010), pp. 549–556. IFAAMAS (2010)

    Google Scholar 

  22. Parunak, H.V.D., Brueckner, S.: Synthetic pheromones for distributed motion control. In: Proceedings of DARPA-JFACC Technical Symposium on Advances in Enterprise Control, DARPA (1999)

    Google Scholar 

  23. Parunak, H.V.D., Brueckner, S.: Concurrent modeling of alternative worlds with polyagents. In: Antunes, L., Takadama, K. (eds.) MABS 2006. LNCS (LNAI), vol. 4442, pp. 128–141. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76539-4_10

    Chapter  Google Scholar 

  24. Parunak, H.V.D., Brueckner, S., Downs, E.A., Sappelsa, L.: Swarming estimation of realistic mental models. In: Giardini, F., Amblard, F. (eds.) MABS 2012. LNCS (LNAI), vol. 7838, pp. 43–55. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38859-0_4

  25. Parunak, H.V.D., Brueckner, S.A.: Engineering swarming systems. In: Bergenti, F., Gleizes, M.-P., Zambonelli, F. (eds.) Methodologies and Software Engineering for Agent Systems, pp. 341–376. Kluwer (2004)

    Google Scholar 

  26. Parunak, H.V.D., Greanya, J., Morell, J.A., Nadella, S., Sappelsa, L.: SCAMP’s stigmergic model of social conflict. Comput. Math. Organ. Theory (2021). https://doi.org/10.1007/s10588-021-09347-8

  27. Pynadath, D.V., et al.: Disaster World: Decision-theoretic agents for simulating population responses to hurricanes. Comput. Math. Organ. Theory (2021). (forthcoming)

    Google Scholar 

  28. Rager, S., Leung, A., Pinegar, S., Mangels, J., Poole, M.S., Contractor, N.: Groups, governance, and greed: the ACCESS world model. Comput. Math. Organ. Theory. (2021). https://doi.org/10.1007/s10588-021-09352-x

  29. Richards, W., Finlayson, M.A., Winston, P.H.: Advancing computational models of narrative. MIT-CSAIL-TR-2009–063, MIT CSAIL, Cambridge (2009)

    Google Scholar 

  30. Sappelsa, L., Parunak, H.V.D., Brueckner, S.: The generic narrative space model as an intelligence analysis tool. Am. Intell. J. 31(2), 69–78 (2014)

    Google Scholar 

  31. Savage, E.L., Schruben, L.W., Yücesan, E.: On the generality of event-graph models. INFORMS J. Comput. 17(1), 3–9 (2005)

    Article  MathSciNet  Google Scholar 

  32. Shapiro, B.P., van den Broek, P., Fletcher, C.R.: Using story-based causal diagrams to analyze disagreements about complex events. Discourse Process. 20(1), 51–77 (1995)

    Article  Google Scholar 

  33. Sheyner, O.M.: Scenario graphs and attack graphs. Thesis at Carnegie Mellon University, Department of Computer Science Department (2004)

    Google Scholar 

  34. Shivashankar, V.: Hierarchical goal networks: formalisms and algorithms for planning and acting. Thesis at University of Maryland, Department of Computer Science (2015)

    Google Scholar 

  35. Sullivan, K., Coletti, M., Luke, S.: GeoMASON: Geospatial support for MASON. George Mason University, Fairfax (2010). https://www.researchgate.net/publication/235955903_GeoMason_Geospatial_Support_for_MASON

  36. Züfle, A., et al.: Urban life: a model of people and places. Comput. Math. Organ. Theory (2021). https://doi.org/10.1007/s10588-021-09348-7

Download references

Acknowledgements

The development of SCAMP was funded by the Defense Advanced Research Projects Agency (DARPA), under Cooperative Agreement HR00111820003. The content of this paper does not necessarily reflect the position or the policy of the US Government, and no official endorsement should be inferred.

Author information

Authors and Affiliations

  1. Parallax Advanced Research, Beavercreek, OH, 45431, USA

    H. Van Dyke Parunak

Authors
  1. H. Van Dyke Parunak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to H. Van Dyke Parunak .

Editor information

Editors and Affiliations

  1. Imperial College London, London, UK

    Koen H. Van Dam

  2. Toulouse 1 Capitole University, Toulouse, France

    Nicolas Verstaevel

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Parunak, H.V.D. (2022). Social Simulation for Non-hackers. In: Van Dam, K.H., Verstaevel, N. (eds) Multi-Agent-Based Simulation XXII. MABS 2021. Lecture Notes in Computer Science(), vol 13128. Springer, Cham. https://doi.org/10.1007/978-3-030-94548-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-94548-0_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94547-3

  • Online ISBN: 978-3-030-94548-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation