AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY

Tibor Bosse, Charlotte Gerritsen, Michel C. A. Klein

2009

Abstract

Criminal behaviour exists in many variations, each with its own cause. A large group of offenders only shows criminal behaviour during adolescence. This kind of behaviour is largely influenced by the interaction with others, through social learning. This paper contributes a dynamical agent-based approach to simulate social learning of adolescence-limited criminal behaviour, illustrated for a small school class. The model is designed in such a way that it can be compared with data resulting from a large scale empirical study.

References

  1. Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ, Prentice-Hall.
  2. Bosse, T., and Gerritsen, C., Agent-Based Simulation of the Spatial Dynamics of Crime: On the Interplay between Criminal Hot Spots and Reputation. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multi-Agent Systems, AAMAS'08. ACM Press, 2008, pp. 1129-1136.
  3. Bosse, T., Jonker, C.M., Meij, L. van der, and Treur, J. (2007). A Language and Environment for Analysis of Dynamics by SimulaTiOn. International Journal of AI Tools, vol. 16, issue 3, pp. 435-464.
  4. Bosse, T., Jonker, C.M., Meij, L. van der, Sharpanskykh, A., and Treur, J. (2006). Specification and Verification of Dynamics in Cognitive Agent Models. In: Proceedings of the 6th International Conference on Intelligent Agent Technology, IAT'06. IEEE Computer Society Press, 2006, pp. 247-254.
  5. Bruinsma, G.J.N. (1985). Crime as Social Learning Process. A Test of the Differential Association Theory in the version of K.-D. Opp (in Dutch). Gouda Quint, Arnhem.
  6. Burgess, R., and Akers, R.L. (1966). A Differential Association-Reinforcement Theory of Criminal Behavior. Social Problems, vol. 14, pp. 363-383.
  7. Chamley, C.P. (2003). Rational Herds: Economic Models of Social Learning. New York: Cambridge University Press.
  8. Conte, R., and Paolucci, M. (2001). Intelligent Social Learning. Journal of Artificial Societies and Social Simulation, vol. 4, issue 1.
  9. Dijkum, C. van, and Landsheer, H. (2000). Experimenting with a Nonlinear Dynamic Model of Juvenile Criminal Behavior. Simulation & Gaming, vol. 31, pp. 479-490.
  10. Gottfredson, M. and Hirschi, T. (1990). A General Theory of Crime. Stanford University Press.
  11. Lanier, M.M., and Henry, S. (1998). Essential Criminology. Boulder, CO: Westview Press.
  12. Liu, L., Wang, X., Eck, J., and Liang, J. (2005). Simulating Crime Events and Crime Patterns in RA/CA Model. In F. Wang (ed.), Geographic Information Systems and Crime Analysis. Singapore: Idea Group, pp. 197-213.
  13. Moffitt, T.E. (1993). Adolescence-Limited and LifeCourse-Persistent Antisocial Behavior: A Developmental Taxonomy. Psychological Review, vol. 100, no. 4, pp. 674-701.
  14. Opp, K.D. (1989). The Economics of Crime and the Sociology of Deviant Behaviour - A Theoretic Confrontation of Basic Propositions. Kyklos, vol. 42, issue 3, pp. 405-430.
  15. Sutherland, E.H., and Cressey, D.R. (1966). Principles of Criminology, 7th edition. Philadelphia: J.B. Lippincott.
  16. Thornberry, T.P., Lizotte, A.J., Krohn, M.D., Farnworth, M., and Jang, S.J. (1994). Delinquent Peers, Beliefs, and Delinquent Behavior: A Longitudinal Test of Interactional Theory. Criminology, vol. 32, pp. 47-83.
  17. Tsvetovat, M., and Carley, K.M. (2005). Structural Knowledge and Success of Anti-Terrorist Activity: The Downside of Structural Equivalence. Journal of Social Structure, vol. 6.
  18. Weerman, F.M., and Bijleveld, C.C.J.H. (2007). Birds of Different Feathers. European Journal of Criminology, vol. 4, issue 4, pp. 357-383.
  19. Winoto, P. (2002). An Agent-Based Simulation of the Market for Offenses. In: AAAI Workshop on MultiAgent Modeling and Simulation of Economic Systems. Edmonton, Canada.
Download


Paper Citation


in Harvard Style

Bosse T., Gerritsen C. and C. A. Klein M. (2009). AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 5-13. DOI: 10.5220/0001512000050013


in Bibtex Style

@conference{icaart09,
author={Tibor Bosse and Charlotte Gerritsen and Michel C. A. Klein},
title={AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY },
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={5-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001512000050013},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY
SN - 978-989-8111-66-1
AU - Bosse T.
AU - Gerritsen C.
AU - C. A. Klein M.
PY - 2009
SP - 5
EP - 13
DO - 10.5220/0001512000050013


in Harvard Style

Bosse T., Gerritsen C. and C. A. Klein M. (2009). AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY .In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 5-13. DOI: 10.5220/0001512000050013


in Bibtex Style

@conference{icaart09,
author={Tibor Bosse and Charlotte Gerritsen and Michel C. A. Klein},
title={AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY },
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={5-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001512000050013},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - AGENT-BASED SIMULATION OF SOCIAL LEARNING IN CRIMINOLOGY
SN - 978-989-8111-66-1
AU - Bosse T.
AU - Gerritsen C.
AU - C. A. Klein M.
PY - 2009
SP - 5
EP - 13
DO - 10.5220/0001512000050013