Tactical Exploration of Tax Compliance Decisions in Multi-agent Based Simulation

  • Luis Antunes
  • João Balsa
  • Ana Respício
  • Helder Coelho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4442)


Tax compliance is a field that crosses over several research areas, from economics to machine learning, from sociology to artificial intelligence and multi-agent systems. The core of the problem is that the standing general theories cannot even explain why people comply as much as they do, much less make predictions or support prescriptions for the public entities. The compliance decision is a challenge posed to rational choice theory, and one that defies the current choice mechanisms in multi-agent systems. The key idea of this project is that by considering rationally-heterogeneous agents immersed in a highly social environment we can get hold of a better grasp of what is really involved in the individual decisions. Moreover, we aim at understanding how those decisions determine tendencies for the behaviour of the whole society, and how in turn those tendencies influence individual behaviour. This paper presents the results of some exploratory simulations carried out to uncover regularities, correlations and trends in the models that represent first and then expand the standard theories on the field. We conclude that forces like social imitation and local neighbourhood enforcement and reputation are far more important than individual perception of expected utility maximising, in what respects compliance decisions.


Central Authority Ethical Attitude Social Simulation Internal Revenue Service Target Phenomenon 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Allingham, M.G., Sandmo, A.: Income tax evasion: A theoretical analysis. Journal of Public Economics 1(3/4), 323–338 (1972)CrossRefGoogle Scholar
  2. 2.
    Andreoni, J., Erard, B., Feinstein, J.: Tax compliance. Journal of Economic Literature 36(2) (1998)Google Scholar
  3. 3.
    Antunes, L., Balsa, J., Moniz, L., Urbano, P., Palma, C.R.: Tax compliance in a simulated heterogeneous multi-agent society. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Antunes, L., Coelho, H.: On how to conduct experiments with self-motivated agents. In: Lindemann, G., Moldt, D., Paolucci, M. (eds.) RASTA 2002. LNCS (LNAI), vol. 2934, Springer, Heidelberg (2004)Google Scholar
  5. 5.
    Antunes, L., Coelho, H., Balsa, J., Respício, A.: e*plore v.0: Principia for strategic exploration of social simulation experiments design space. In: Proceedings of The First World Congress on Social Simulation, Kyoto, Japan (2006)Google Scholar
  6. 6.
    Antunes, L., Del Gaudio, R., Conte, R.: Towards a gendered-based agent model. In: Proceedings of Agent 2004 Conference on Social Dynamics: Interaction, Reflexivity and Emergence, Chicago, USA (2004)Google Scholar
  7. 7.
    Balsa, J., Antunes, L., Respício, A., Coelho, H.: Autonomous inspectors in tax compliance simulation. In: Proceedings of the 18th European Meeting on Cybernetics and Systems Research (2006)Google Scholar
  8. 8.
    Boadway, R., Marceau, N., Mongrain, S.: Tax evasion and trust. Technical Report 104, Center for Research on Economic Fluctuations and Employment, Université du Québec à Montréal (February 2000)Google Scholar
  9. 9.
    Castelfranchi, C.: Guarantees for autonomy in cognitive agent architecture. In: Wooldridge, M.J., Jennings, N.R. (eds.) Intelligent Agents. LNCS, vol. 890, Springer, Heidelberg (1995)Google Scholar
  10. 10.
    Conte, R., Gilbert, N.: Introduction: computer simulation for social theory. In: Gilbert, N., Conte, R. (eds.) Artificial Societies: the computer simulation of social life, UCL Press, London, UK (1995)Google Scholar
  11. 11.
    Gilbert, N.: Models, processes and algorithms: Towards a simulation toolkit. In: Suleiman, R., Troitzsch, K.G., Gilbert, N. (eds.) Tools and Techniques for Social Science Simulation, Physica-Verlag, Heidelberg (2000)Google Scholar
  12. 12.
    Gilbert, N., Doran, J. (eds.): Simulating Societies: the computer simulation of social phenomena. In: Proceedings of SimSoc 1992. UCL Press, London (1992)Google Scholar
  13. 13.
    Gilbert, N., Doran, J. (eds.): Simulating Societies: the computer simulation of social phenomena. UCL Press, London (1994)Google Scholar
  14. 14.
    Hewitt, C.: Viewing control as patterns of passing messages. Artificial Intelligence 8 (1977)Google Scholar
  15. 15.
    Hewitt, C.: The challenge of open systems. Byte (April 1985)Google Scholar
  16. 16.
    Kaplan, F.: The emergence of a lexicon in a population of autonomous agents (in French). PhD thesis, Université de Paris 6 (2000)Google Scholar
  17. 17.
    Myles, G.D., Naylor, R.A.: A model of tax evasion with group conformity and social customs. European Journal of Political Economy 12(1), 49–66 (1996), CrossRefGoogle Scholar
  18. 18.
    Simon, H.: Rationality in psychology and economics. In: Hogarth, R.M., Reder, M.W. (eds.) Rational choice: the Contrast Between Economics and Psychology, Univ. of Chicago Press (1987)Google Scholar
  19. 19.
    Urbano, P.: Decentralised Consensus Games (in Portuguese). PhD thesis, Faculdade de Ciências da Universidade de Lisboa (2004)Google Scholar
  20. 20.
    Wintrobe, R.: K. Gërxhani. Tax evasion and trust: a comparative analysis. In: Proceedings of the Annual Meeting of the European Public Choice Society – EPCS 2004 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Luis Antunes
    • 1
  • João Balsa
    • 1
  • Ana Respício
    • 1
  • Helder Coelho
    • 1
  1. 1.GUESS/Universidade de LisboaPortugal

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