Using difference equations to find optimal tax structures on the SugarScape

Journal of Economic Interaction and Coordination

Volumn 9, Issue 2, 2014, Pages 233-253

  Oremland, Matthew ^a   Laubenbacher, Reinhard ^b  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^b UNIVERSITY OF CONNECTICUT HEALTH CENTER   (United States)

Author keywords

Approximation; Difference equations; Optimization; SugarScape

Indexed keywords

EID: 84908217055     PISSN: 1860711X     EISSN: 18607128     Source Type: Journal    
DOI: 10.1007/s11403-014-0133-5     Document Type: Article

References (33)

1. Castiglione F, Pappalardo F, Bernaschi M, Motta S (2007) Optimization of HAART with genetic algorithms and agent-based models of HIV infection. Bioinformatics 23(24):3350–3355
2. Cecconi F, Campenni M, Andrighetto G, Conte R (2010) What do agent-based and equation-based modelling tell us about social conventions: the clash between abm and ebm in a congestion game framework. J Artif Soc Soc Simul 13(1):6
3. Coello C (2013) List of references on evolutionary multiobjective optimization. http://www.lania.mx/ccoello/EMOO/EMOObib.html. Archived at http://www.webcitation.org/6HhFo4K5H
4. Dascàlu M, Franti E, Stefan G (1998) Modeling production with artificial societies: the emergence of social structure. In: Serra R, Liverani F, Bandini S (eds) Cellular automata: research towards industry. Springer, London, pp 218–229
5. Dean JS, Gumerman GJ, Epstein JM, Axtell RL, Swedlund AC, Parker MT, McCarroll S (2000) Understanding anasazi culture change through agent-based modeling. Dynamics in human and primate societies. Oxford University Press, Oxford, pp 179–206
6. Ding W, Gross LJ, Langston K, Lenhart S, Real LA (2007) Rabies in raccoons: optimal control for a discrete time model on a spatial grid. J Biol Dyn 1(4):379–393
7. Duboz R, Ramat É, Preux P (2003) Scale transfer modeling: using emergent computation for coupling an ordinary differential equation system with a reactive agent model. Syst Anal Model Simul 43(6):793–814
8. Edwards M, Huet S, Goreaud F, Deffuant G (2003) Comparing an individual-based model of behavior diffusion with its mean field aggregate approximation. J Artif Soc Soc Simul 6(4):3.4–3.8
9. Epstein JM, Axtell R (1996) Growing artificial societies: social science from the bottom up. Brookings Institute, Washington
10. Fahse L, Wissel C, Grimm V (1998) Reconciling classical and individual-based approaches in theoretical population ecology: a protocol for extracting population parameters from individual-based models. Am Nat 152(6):838–852
11. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198(1–2):115–126
12. Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221(23):2760–2768
13. Hayek N (2011) Infinite horizon multiobjective optimal control problems in the discrete time case. Optimization 60(4):509–529
14. Hinkelmann F, Murrugarra D, Jarrah A, Laubenbacher R (2011) A mathematical framework for agent based models of complex biological networks. Bull Math Biol 73(7):1583–1602
15. Huet S, Edwards M, Deffuant G (2007) Taking into account the variations of neighbourhood sizes in the mean-field approximation of the threshold model on a random network. J Artif Soc Soc Simul 10(1):1.1–5.5
16. Kasaie P, Kelton W, Vaghefi A, Naini S (2010) Toward optimal resource-allocation for control of epidemics: an agent-based-simulation approach. In: Winter Simulation Conference (WSC), Proceedings of the 2010, pp 2237–2248
17. Laubenbacher R, Hinkelmann F, Oremland M (2013) Agent-based models and optimal control in biology: a discrete approach. In: Robeva R, Hodge TL (eds) Mathematical concepts and methods in modern biology. Academic Press, Boston, pp 143–178
18. Lenhart S, Workman J (2007) Optimal control applied to biological models. Chapman and Hall/CRC, Boca Raton
19. Lollini PL, Motta S, Pappalardo F (2006) Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator. BMC Bioinform 7:352
20. Luke S, Cioffi-Revilla C, Panait L, Sullivan K, Balan G (2005) MASON: a multi-agent simulation environment. Simul Trans Soc Model Simul Int 82(7):517–527
21. Mao L (2011) Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks. BMC Public Health 11:522
22. Moore H (1897) Cours d’économie politique. by Vilfredo Pareto, professeur à l’Université de Lausanne. Vol. i. pp. 430. i896. Vol. ii. pp. 426. i897. Lausanne: F. Rouge. The ANNALS of the American Academy of Political and Social Science 9(3):128–131
23. North MJ, Collier NT, Vos JR (2006) Experiences creating three implementations of the repast agent modeling toolkit. ACM Trans Model Comput Simul 16(1):1–25
24. Okell LC, Drakeley CJ, Bousema T, Whitty CJ, Ghani AC (2008) Modelling the impact of artemisinin combination therapy and long-acting treatments on malaria transmission intensity. PLoS Med 5:e226 discussion e226
25. Ovaskainen O, Cornell SJ (2006) Space and stochasticity in population dynamics. Proc Natl Acad Sci USA 103(34):12,781–12,786
26. Pappalardo F, Pennisi M, Castiglione F, Motta S (2010) Vaccine protocols optimization: in silico experiences. Biotechnol Adv 28:82–93
27. Parunak H, Savit R, Riolo RL (1998) Agent-based modeling versus equation-based modeling: a case study and users guide. In: Sichman JS, Conte R, Gilbert N (eds) Multi-agent systems and agent-based simulation, Lecture notes in computer science, vol 1534. Springer, Berlin, pp 10–25
28. Pennisi M, Catanuto R, Pappalardo F, Motta S (2008) Optimal vaccination schedules using simulated annealing. Bioinformatics 24:1740–1742
29. Picard N, Franc A (2001) Aggregation of an individual-based space-dependent model of forest dynamics into distribution-based and space-independent models. Ecol Model 145(1):69–84
30. Rahman A, Setayeshi S, Shamsaei M (2007) An analysis to wealth distribution based on sugarscape model in an artificial society. Int J Eng 20(3):211–224
31. Rahmandad H, Sterman J (2008) Heterogeneity and network structure in the dynamics of diffusion: comparing agent-based and differential equation models. Manag Sci 54(5):998–1014
32. Wilensky U (2009) Netlogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL, http://ccl.northwestern.edu/netlogo/
33. Yang Y, Atkinson PM, Ettema D (2011) Analysis of CDC social control measures using an agent-based simulation of an influenza epidemic in a city. BMC Infect Dis 11:199