Disentangling Cognitive and Constructivist Aspects of Hierarchies

Stefano Bennati

Abstract

One of the most puzzling problems in the social sciences is the emergence of social institutions. The field of sociology is trying to understand why our society is the way we know it and whether an alternative, possibly better, society would be possible. One of the fundamental questions is the emergence of hierarchies. The cognitive approach suggests that hierarchies are encoded in human nature, therefore are the most natural form of organization; on the other hand the costructivist approach sees hierarchies as a product of interactions between individuals that emerges independently of individual preferences. We will investigate under which conditions hierarchies emerge from a cognitive factor, a constructivist factor or a combination of both. We will study this question both at the analytic level, with the help of Agent-Based simulations where agents are Neural Networks, and at the empirical level by running sociological experiments in our laboratory.

References

  1. Axelrod, R. (1980). Effective choice in the prisoner's dilemma. Journal of conflict resolution, 24(1):3-25.
  2. Axelrod, R. M. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton University Press.
  3. Axtell, R., Epstein, J. M., and Young, H. P. (2000). The emergence of classes in a multi-agent bargaining model.
  4. Gould, R. V. (2002). The origins of status hierarchies: A formal theory and empirical test1. American journal of sociology, 107(5):1143-1178.
  5. Halevy, N., Chou, E. Y., and Galinsky, A. D. (2011). A functional model of hierarchy why, how, and when vertical differentiation enhances group performance. Organizational Psychology Review, 1(1):32-52.
  6. Helbing, D. and Yu, W. (2009). The outbreak of cooperation among success-driven individuals under noisy conditions. Proceedings of the National Academy of Sciences, 106(10):3680-3685.
  7. Lashley, K. S. (1929). Brain mechanisms and intelligence: A quantitative study of injuries to the brain.
  8. Lemke, J. L. (2000). Across the scales of time: Artifacts, activities, and meanings in ecosocial systems. Mind, culture, and activity, 7(4):273-290.
  9. Paine, R. W. and Tani, J. (2005). How hierarchical control self-organizes in artificial adaptive systems. Adaptive Behavior, 13(3):211-225.
  10. Pessa, E. (2009). Self-organization and emergence in neural networks. Electronic Journal of Theoretical Physics, 6(20):269-306.
  11. Schmidhuber, J. (1990). Dynamische neuronale Netze und das fundamentale raumzeitliche Lernproblem.
  12. Schmidhuber, J., Wierstra, D., Gagliolo, M., and Gomez, F. (2007). Training recurrent networks by evolino. Neural Computation, 19(3):757-779.
  13. Siegelmann, H. T. and Sontag, E. D. (1991). Turing computability with neural nets. Applied Mathematics Letters, 4(6):77-80.
  14. Siegelmann, H. T. and Sontag, E. D. (1995). On the computational power of neural nets. Journal of computer and system sciences, 50(1):132-150.
  15. Simon, H. A. (1977). The organization of complex systems. In Models of Discovery, pages 245-261. Springer.
Download


Paper Citation


in Harvard Style

Bennati S. (2015). Disentangling Cognitive and Constructivist Aspects of Hierarchies . In Doctoral Consortium - DCAART, (ICAART 2015) ISBN , pages 10-14


in Bibtex Style

@conference{dcaart15,
author={Stefano Bennati},
title={Disentangling Cognitive and Constructivist Aspects of Hierarchies},
booktitle={Doctoral Consortium - DCAART, (ICAART 2015)},
year={2015},
pages={10-14},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DCAART, (ICAART 2015)
TI - Disentangling Cognitive and Constructivist Aspects of Hierarchies
SN -
AU - Bennati S.
PY - 2015
SP - 10
EP - 14
DO -