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Types of Simulation

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Simulating Social Complexity

Part of the book series: Understanding Complex Systems ((UCS))

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Notes

  1. 1.

    This distinction is of course not set in stone. For an example of an evidence-driven approach to computer simulation see Chap. 25 in this volume (Geller and Moss 2013).

  2. 2.

    http://www.simport.eu/

References

  • Amblard F, Quattrociocchi W (2013) Social networks and spatial distribution. Chapter 16 in this volume

    Google Scholar 

  • Anderson JR et al (2004) An integrated theory of the mind. Psychol Rev 111(4):1036–1060

    Article  Google Scholar 

  • Barreteau O et al (2013) Participatory approaches. Chapter 10 in this volume

    Google Scholar 

  • Bazzan ALC, Bordini RH (2001) A framework for the simulation of agents with emotions: report on experiments with the iterated prisoners dilemma. In fifth international conference on autonomous agents, Montreal. ACM Press, New York, pp 292–299

    Google Scholar 

  • Bratman ME (1987) Intentions, plans, and practical reason. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Broersen J, Dastani M, Huang Z, Hulstijn J, Van der Torre L (2001) The BOID architecture: conflicts between beliefs, obligations, intentions and desires. In fifth international conference on autonomous agents, Montreal. ACM Press, New York, pp 9–16

    Google Scholar 

  • Chen D et al (2008) Large-scale agent-based simulation on the grid. Future Gen Comput Syst 24(7):658–671

    Article  Google Scholar 

  • Conte R, Gilbert N (eds) (1995) Artificial societies: the computer simulation of social life. UCL Press, London

    Google Scholar 

  • David N (2013) Validating simulations. Chapter 8 in this volume

    Google Scholar 

  • 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, 1979). Springer, Berlin, pp 98–107

    Google Scholar 

  • Dignum V (2013) Organisational design. Chapter 20 in this volume

    Google Scholar 

  • Edmonds B, Lucas P, Rouchier J, Taylor R (2013) Human societies: understanding observed social phenomena. Chapter 26 in this volume

    Google Scholar 

  • Gardner M (1970) Mathematical games: the fantastic combinations of John Conway’s new solitaire game “Life”. Sci Am 223(4):120–124

    Article  Google Scholar 

  • Geller A, Moss S (2013) Modeling power and authority: an emergentist view from Afghanistan. Chapter 25 in this volume

    Google Scholar 

  • Georgeff M, Pell B, Pollack M, Tambe M, Wooldridge M (1998) The belief-desire-intention model of agency. In: Muller J, Singh M, Rao A (eds) Intelligent agents V (Lecture notes in artificial intelligence, 1555). Springer, Berlin, pp 1–10

    Google Scholar 

  • Gilbert N (2006) When does social simulation need cognitive models? In: Sun R (ed) Cognition and multi-agent interaction: from cognitive modelling to social simulation. Cambridge University Press, Cambridge, pp 428–432

    Google Scholar 

  • Gilbert N, Doran J (eds) (1994) Simulating societies. UCL Press, London

    Google Scholar 

  • Gilbert N, Troitzsch KG (2005) Simulation for the social scientist, 2nd edn. Open University Press/McGraw Hill Education, Maidenhead

    Google Scholar 

  • Gilbert N, Pyka A, Ahrweiler P (2001) Innovation networks: a simulation approach. J Artif Soc Soc Simulat 4(3). http://jasss.soc.surrey.ac.uk/4/3/8.html

  • Grimm V et al (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198:115–126

    Article  Google Scholar 

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

    Google Scholar 

  • Hales D (2013) Distributed computer systems. Chapter 21 in this volume

    Google Scholar 

  • Hemelrijk C (2013) Animal social behaviour. Chapter 22 in this volume

    Google Scholar 

  • 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 Simulat 2(2). http://jasss.soc.surrey.ac.uk/2/2/2.html

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

    Article  Google Scholar 

  • Le Page C et al (2013) Environmental management. Chapter 19 in this volume

    Google Scholar 

  • Massaguer D, Balasubramanian V, Mehrotra S, Venkatasubramanian N (2006) Multi-agent simulation of disaster response. In: Jennings NR, Tambe M, Ishida T, Ramchurn SD (eds) First international workshop on agent technology for disaster management. Hakodate, 8 May 2006, pp 124–130. http://users.ecs.soton.ac.uk/sdr/atdm/ws34atdm.pdf

  • Méndez G, Rickel J, de Antonio A (2003) Steve meets jack: the integration of an intelligent tutor and a virtual environment with planning capabilities. In: intelligent virtual agents (Lecture notes on artificial intelligence, 2792). Springer, Berlin, pp 325–332

    Google Scholar 

  • Newell A (1994) Unified theories of cognition. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Railsback SF, Grimm V (2011) Agent-based and individual-based modeling: a practical introduction. Princeton University Press, Princeton

    Google Scholar 

  • Railsback SF, Lytinen SL, Jackson SK (2006) Agent-based simulation platforms: review and development recommendations. Simulation 82(9):609–623

    Article  Google Scholar 

  • Ramstedt L, Törnquist Krasemann J, Davidsson P (2013) Movement of people and goods. Chapter 24 in this volume

    Google Scholar 

  • Reynolds CW (1987) Flocks, herds, and schools: a distributed behavioural model. Comput Graph 21(4):25–34

    Article  Google Scholar 

  • Rouchier J (2013) Markets. Chapter 23 in this volume

    Google Scholar 

  • Sawyer RK (2003) Artificial societies: multi-agent systems and the micro–macro link in sociological theory. Sociol Methods Res 31(3):325–363

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  • Schiff JL (2008) Cellular automata: a discrete view of the world. Wiley, Oxford

    MATH  Google Scholar 

  • Schüle M, Herrler R, Klügl F (2004) Coupling GIS and multi-agent simulation: towards infrastructure for realistic simulation. In: Lindemann G, Denzinger J, Timm IJ, Unland R (eds) Multiagent system technologies, second German conference, MATES 2004 (LNCS, 3187). Springer, Berlin, pp 228–242

    Google Scholar 

  • Verhagen H (2001) Simulation of the learning of norms. Soc Sci Comput Rev 19(3):296–306

    Article  Google Scholar 

  • Williams R (1993) An agent based simulation environment for public order management training. In: Western simulation multiconference, object-oriented simulation conference, Hyatt Regency, La Jolla, 17–20 Jan 1993, pp 151–156

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Malmö University, Malmö, Sweden

    Paul Davidsson

  2. Stockholm University, Stockholm, Sweden

    Harko Verhagen

Authors
  1. Paul Davidsson
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  2. Harko Verhagen
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Corresponding author

Correspondence to Paul Davidsson .

Editor information

Editors and Affiliations

  1. CPM - Centre for Policy Modelling, Manchester Metropolitan University, Manchester, M1 3GH, United Kingdom

    Bruce Edmonds

  2. , Center for Policy Modelling, Manchester Metropolitan University, Aytoun Street, Manchester, M1 3GH, United Kingdom

    Ruth Meyer

Further Reading

Further Reading

Gilbert and Troitzsch (2005) also have sections that describe the different kinds of simulation available. Railsback and Grimm (2011) present a complementary analysis, coming from ecological modelling. The introductory chapters in (Gilbert and Doran 1994) and (Conte and Gilbert 1995) map out many of the key issues and aspects in which social simulation has developed.

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Davidsson, P., Verhagen, H. (2013). Types of Simulation. In: Edmonds, B., Meyer, R. (eds) Simulating Social Complexity. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93813-2_3

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  • DOI: https://doi.org/10.1007/978-3-540-93813-2_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-93812-5

  • Online ISBN: 978-3-540-93813-2

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