Simulating crime against properties using swarm intelligence and social networks

Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems

Volumn , Issue , 2008, Pages 300-318

  Furtado, Vasco ^a   Melo, Adriano ^a   Coelho, André L V ^a   Menezes, Ronaldo ^a,b   Belchior, Mairon ^a  

^a UNIVERSITY OF FORTALEZA   (Brazil)

^b FLORIDA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84901554243     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-591-7.ch015     Document Type: Chapter

References (17)

1. Akers, R., Krohn, M., Lanza-Kaduce, L., & Radosevich, M. (1979). Social learning and deviant behavior: A specific test of a general theory. American Sociological Review, 44,(4), 636-655.
2. Barabási, A. (2002). Linked: The new science of networks. Cambridge: Perseus Pulishing.
3. Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems. Santa Fe Institute Studies in the Sciences of Complexity Series: Oxford Press.
4. Brantingham, P., & Brantingham, P. (1979). Environment, routine, and situation: Toward a pattern theory of crime. In R. Clark & M. Felson (Eds.), Routine activity and rational choice (Vol. 5) (pp. 259 - 294).Transaction Books
5. Buchanan, M. (2002). Nexus: Small worlds and the groundbreaking science of networks. New York: W. W. Norton.
6. Calvó-Armengol, A., & Zenou, Y. (2004). Social networks and crime decisions: The role of social structure in facilitating delinquent behavior. International Economic Review, 45(3), 939-58.
7. Cansado, T. M. L. (2005). Alocação e despacho de recursos para combate à criminalidade. Master dissertation, UFMG, Belo Horizonte.
8. th European Workshop on on Modelling Autonomous Agents in a Multi-Agent World, Artificial Social Systems (MAAMAW), Lecture Notes in Computer Science (Vol. 830, pp. 3-23).
9. Gilbert, N., & Conte, R. (1995). Artificial societies: The computer simulation of social life. London: UCL Press.
10. Glaeser, E., Sacerdote, B., & Scheinkman, J. (1996, May). Crime and social interactions. Quarterly Journal of Economics, 111(2), 507-48.
11. Houtzager, B., & Baerveldt, C. (1999). Just like normal: A social network study of the relation between petty crime and the intimacy of adolescent friendships. Social Behavior and Personality, 27(2), 117-192.
12. Java Universal Network/Graph Framework. Retrieved September 6, 2007, from http://jung.sourceforge.net
13. Kaza, S., Xu, J., Marshall, B., & Chen, H. (2005). Topological analysis of criminal activity networks in multiple jurisdictions.
14. Reis, D., Melo, A., Coelho, A. L. V., & Furtado, V. (2006). GAPatrol: An evolutionary multiagent approach for the automatic definition of hotspots and patrol routes. In J. S. Sichman, H. Coelho, & S. Oliveira (Eds.). In Proceedings of IBERAMIA/SBIA 2006, Lecture Notes in Artificial Intelligence (LNAI) 4140, pp. 118-127.
15. Scott, J. P (2000). Social network analysis: A handbook. Sage Publications.
16. th ed.). Philadelphia: J. B. Lippincott Company.
17. Zipf, G. K. (1949). Human behaviour and the principle of least-effort. Cambridge: Addison-Wesley