Neuroeconomics: Yet Another Field Where Rough Sets Can Be Useful?
We deal with neuroeconomics which may be viewed as a new emerging field of research at the crossroads of economics, or decision making, and brain research. Neuroeconomics is basically about neural mechanisms involved in decision making and their economic relations and connotations. We briefly review first the traditional formal approach to decision making, then discuss some experiments of real life decision making processes and point our when and where the results prescribed by the traditional formal models are not confirmed. We deal with both decision analytic and game theoretic type models. Then, we discuss results of brain investigations which indicate which parts of the brain are activated while performing some decision making related courses of action and provide some explanation about possible causes of discrepancies between the results of formal models and experiments. We point out the role of brain segmentation techniques to determine the activation of particular parts of the brain, and point out that the use of some rough sets approaches to brain segmentation, notably by Hassanien, Ślȩzak and their collaborators, can provide useful and effective tool.
Unable to display preview. Download preview PDF.
- 1.Camerer, C.F.: Psychology and economics. Strategizing in the brain 300, 1673–1675 (2003)Google Scholar
- 3.Glimcher, P.W.: Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics. MIT Press, Cambridge (2003)Google Scholar
- 9.Kahneman, D., Slovic, P., Tversky, A. (eds.): Judgment under Uncertainty: Heuristics and Biases. Cambridge University Press, Cambridge (1982)Google Scholar
- 11.Kenning, P., Plassmann, H.: NeuroEconomics: An Overview from an Economic Prespective. Brain Reserach Nulletin 67, 343–354 (2005)Google Scholar
- 12.McCabe, K.: Neuroeconomics. In: Nadel, L. (ed.) Encyclopedia of Cognitive Science, pp. 294–298. Wiley, New York (2005)Google Scholar
- 16.Poundstone, W.: Prisoner’s Dilemma. Doubleday, New York (1992)Google Scholar
- 17.Ramirez, L., Durdle, N.G., Raso, V.J.: Medical image registration in computational intelligence framework: a review. In: Proceedings of IEEE–CCECE 2003: Canadian Conference on Electrical and Computer Engineering, vol. 2, pp. 1021–1024 (2003)Google Scholar
- 18.Robbins, L.: An Essay on the Nature and Significance of Economic Science. Macmillan, London (1932)Google Scholar
- 19.Ross, D.: Economic Theory and Cognitive Science: Microexplanation. MIT Press, Cambridge (2005)Google Scholar
- 20.Rubinstein, A.: Comments on Behavioral Economics. In: Blundell, Newey, W.K., Persson, T. (eds.) Advances in Economic Theory (2005 World Congress of the Econometric Society), vol. II, pp. 246–254. Cambridge University Press, Cambridge (2006)Google Scholar
- 22.Sutton, R.S., Barto, A.G. (eds.): Reinforcement Learning: An Introduction. Adaptive Computation and Machine Learning. MIT Press, Cambridge (1998)Google Scholar
- 24.Widz, S., Revett, K., Ślȩzak, D.: A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts. In: Ślȩzak, D., Yao, J.T., Peters, J.F., Ziarko, W., Huo, X. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3642, pp. 372–382. Springer, Heidelberg (2005)CrossRefGoogle Scholar