Skip to main content
SpringerLink
Log in
Book cover

Computational Complexity pp 2999–3003Cite as

Social Phenomena Simulation

  • Reference work entry

  • 296 Accesses

Article Outline

Glossary

Definition of the Subject

Introduction

Why Simulate Social Phenomena?

Simulating Social Phenomena

Future Directions

Further Reading

Bibliography

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   1,500.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   1,399.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Abbreviations

Agent (or software agent ):

A self‐contained entity that has a state and that issituated (able to perceive and act) in an environment. In addition, agents are often assumed to be rational and autonomous.

Cellular automaton :

A mathematical structure modeling a set of cells that interact with theirneighbors. Each cell has a set of neighbors and a state. All the cells update their valuessimultaneously at discrete time steps. The new state of a cell is determined by the current stateof its neighbors according to a local function or rule.

Microlevel simulation :

A type of simulation in which the specific behaviors of specific individuals are explicitlymodeled.

Bibliography

  1. Alexander JC, Giesen B, Münch R, Smelser NJ (eds) (1987) The Micro-Macro Link.University of California Press, Berkeley

    Google Scholar 

  2. Barricelli NA (1957) Symbiogenetic evolution processes realized by artificial methods.Methodos 9(35–36):143–182

    Google Scholar 

  3. Brouwers L, Verhagen H (2004) Applying the Consumat model to flood management policies.In: Müller J, Seidel M (eds) 4th Workshop on Agent-Based Simulation. SCS,Montpellier, pp 29–34

    Google Scholar 

  4. Carley KM, Prietula M (eds) (1994) Computational Organization Theory. Erlbaum, Hillsdale

    Google Scholar 

  5. Davidsson P (2000) Multi-agent-based simulation: beyond social simulation. In: Moss S,Davidsson P (eds) Multi-Agent-Based Simulation. Lecture Notes in Computer Science, vol 1979.Springer, Berlin, pp 98–107

    Google Scholar 

  6. Davidsson P (2002) Agent-based social simulation: a computer science view. J Artif Soc Soc Simul 5(1)

    Google Scholar 

  7. Davidsson P, Holmgren J, Kyhlbäck H, Mengistu D, Persson M (2007) Applications of multi-agent-based simulation. In: Antunes L, Takadama K (eds) Multi-Agent-Based Simulation VII. LectureNotes in Computer Science, vol 4442. Springer, Berlin

    Google Scholar 

  8. Epstein JM, Axtell RL (1996) Growing Artificial Societies: Social Science from theBottom Up. MIT Press, Cambridge

    Google Scholar 

  9. Fiedrich F, Burghardt P (2007) Emergency response information systems: emerging trendsand technologies: agent-based systems for disaster management. Commun ACM 50(3):41–42

    Article  Google Scholar 

  10. Galam S (2008) Sociophysics: a review of Galam models. arXiv:0803.1800 http://arxiv.org/abs/0803.1800. Accessed 06 Aug 2008

  11. Gilbert N (1994) Computer Simulation of Social Processes. Social Research Update, Issue6, Department of Sociology, University of Surrey, UK. http://www.soc.surrey.ac.uk/sru/. Accessed 06 Aug 2008

  12. Gilbert N, Troitzsch KG (2005) Simulation for the Social Scientist, 2nd edn. OpenUniversity Press, Maidenhead

    Google Scholar 

  13. Guye-Vuillème A (2004) Simulation of nonverbal social interaction and small groupsdynamics in virtual environments. Ph D thesis, Ècole Polytechnique Fédérale de Lausanne, No 2933

    Google Scholar 

  14. Janssen MA, Jager W (1999) An Integrated Approach to Simulating Behavioural Processes:A Case Study of the Lock-in of Consumption Patterns. J Artif Soc Soc Simul 2(2)

    Google Scholar 

  15. Künzel J, Hämmer V (2006) Simulation in university education: the artificial agent PSIas a teaching tool. Simulation 82(11):761–768

    Google Scholar 

  16. Lansing JS (2002) “Artificial societies” and the social sciences. Artif Life 8:279–292

    Article  Google Scholar 

  17. Macy MW, Willer R (2002) From factors to actors: computational sociology andagent-based modeling. Annu Rev Sociol 28:143–166

    Article  Google Scholar 

  18. Massaguer D, Balasubramanian V, Mehrotra S, Venkatasubramanian N (2006) Multi-agentsimulation of disaster response. In: Proceedings of the 1st International Workshop on AgentTechnology for Disaster Management 2006. Hakodate

    Google Scholar 

  19. Méndez G, Rickel J, de Antonio A (2003) Steve meets Jack: the integration of anintelligent tutor and a virtual environment with planning capabilities. In: Intelligent VirtualAgents. Lecture Notes on Artificial Intelligence, vol 2792. Springer, Berlin, pp 325–332

    Google Scholar 

  20. Newell A (1994) Unified Theories of Cognition. Harvard University Press, Cambridge

    Google Scholar 

  21. Parunak HVD, Savit R, Riolo RL (1998) Agent-based modeling vs. equation‐basedmodeling: a case study and users' guide. In: Sichman JS, Conte R, Gilbert N (eds) Multi-AgentSystems and Agent-Based Simulation. Lecture Notes in Computer Science, vol 1534. Springer, Berlin,pp 10–26

    Google Scholar 

  22. Prietula MJ, Carley KM, Gasser L (eds) (1998) Simulating Organizations: ComputationalModels of Institutions and Groups. MIT Press, Cambridge

    Google Scholar 

  23. Raney B, Cetin N, Völlmy A, Vrtic M, Axhausen K, Nagel K (2003) An Agent-BasedMicrosimulation Model of Swiss Travel: First Results. J Netw Spatial Econ 3(1):23–41

    Google Scholar 

  24. Reynolds CW (1987) Flocks, herds, and schools: a distributed behavioral model.Comput Graph 21(4):25–34 (SIGGRAPH '87 Conference Proceedings)

    Article  Google Scholar 

  25. Rickel J, Lewis Johnson W (1999) Animated agents for procedural training in virtualreality: perception, cognition, and motor control. Appl Artif Intell 13:343–382

    Article  Google Scholar 

  26. Sawyer RK (2003) Artificial societies – multi-agent systems and the micro-macro linkin sociological theory. Sociol Meth Res 31(3):325–363

    Article  MathSciNet  Google Scholar 

  27. Schelling TC (1971) Dynamic models of segregation. J Math Sociol 1(1):143–186

    Article  Google Scholar 

  28. Stone B (2005) Serious gaming. Def Manag J (31):142–144

    Google Scholar 

  29. Takahashi T (2007) Agent based disaster simulation evaluation and its probability modelinterpretation. In: Proceedings of the 4th International Conference on Intelligent Human‐Computer Systems for CrisisResponse and Management, 2007, Deltft, pp 369–376

    Google Scholar 

  30. Takahashi S, Sallach D, Rouchier J (2007) Advancing Social Simulation – The FirstWorld Congress. Springer, Berlin

    Book  Google Scholar 

  31. Williams R (1993) An agent based simulation environment for public order managementtraining. In: Western Simulation Multiconference, Object‐Oriented Simulation Conference (OOS '93), San Diego151–156

    Google Scholar 

  32. Yergens D, Hiner J, Denzinger J, Noseworthy T (2006) IDESS – A multi-agent-basedsimulation system for rapid development of infectious disease models. Int Trans Syst Sci Appl 1(1):51–58

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Blekinge Institute of Technology, Ronneby, Sweden

    Paul Davidsson

  2. Stockholm University and Royal Institute of Technology, Stockholm, Sweden

    Harko Verhagen

Authors
  1. Paul Davidsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Harko Verhagen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag

About this entry

Cite this entry

Davidsson, P., Verhagen, H. (2012). Social Phenomena Simulation. In: Meyers, R. (eds) Computational Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1800-9_185

Download citation

Publish with us

Policies and ethics

Search

Navigation