Abstract
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.
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References
Camerer, C.F.: Psychology and economics. Strategizing in the brain 300, 1673–1675 (2003)
Camerer, C.F., Loewenstein, G., Prelec, D.: Neuroeconomics: How Neuroscience Can Inform Economics. Journal of Economic Literature XLIII, 9–64 (2005)
Glimcher, P.W.: Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics. MIT Press, Cambridge (2003)
Gŭth W., Schmittberger, R., Schwarze, B.: An Experimental Analysis of Ultimatum Bargaining. Journal of Economic Behavior and Organization 3(4), 367–388 (1982)
Hardy-Vallée, B.: Decision-Making: A Neuroeconomic Perspective. Philosophy Compass 2(6), 939–953 (2007)
Hassanien, A.E.: Fuzzy-rough hybrid scheme for breast cancer detection. Image and Computer Vision 25(2), 172–183 (2007)
Hassanien, A.E., Ślȩzak, D.: Rough Neural Intelligent Approach for Image Classification: A Case of Patients with Suspected Breast Cancer. International Journal of Hybrid Intelligent Systems 3/4, 205–218 (2006)
Kahneman, D.: A Perspective on Judgment and Choice: Mapping Bounded Rationality. American Psychologist 58(9), 697–720 (2003)
Kahneman, D., Slovic, P., Tversky, A. (eds.): Judgment under Uncertainty: Heuristics and Biases. Cambridge University Press, Cambridge (1982)
Kahneman, D., Wakker, P.P., Sarin, R.: Back to Bentham? Explorations of Experienced Utility. The Quarterly Journal of Economics 112(2), 375–397 (1997)
Kenning, P., Plassmann, H.: NeuroEconomics: An Overview from an Economic Prespective. Brain Reserach Nulletin 67, 343–354 (2005)
McCabe, K.: Neuroeconomics. In: Nadel, L. (ed.) Encyclopedia of Cognitive Science, pp. 294–298. Wiley, New York (2005)
Montague, R., King-Casas, B., Cohen, J.D.: Imaging Valuation Models in Human Choice. Annual Review of Neuroscience 29, 417–448 (2006)
Montague, R., Berns, G.S.: Neural Economics and the Biological Substrates of Valuation. Neuron 36(2), 265–284 (2002)
Naqvi, N., Shiv, B., Bechara, A.: The Role of Emotion in Decision Making: A Cognitive Neuroscience Perspective. Current Directions in Psychological Science 15(5), 260–264 (2006)
Poundstone, W.: Prisoner’s Dilemma. Doubleday, New York (1992)
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)
Robbins, L.: An Essay on the Nature and Significance of Economic Science. Macmillan, London (1932)
Ross, D.: Economic Theory and Cognitive Science: Microexplanation. MIT Press, Cambridge (2005)
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)
Samuelson, L.: Economic Theory and Experimental Economics. Journal of Economic Literature 43, 65–107 (2005)
Sutton, R.S., Barto, A.G. (eds.): Reinforcement Learning: An Introduction. Adaptive Computation and Machine Learning. MIT Press, Cambridge (1998)
Tversky, A., Kahneman, D.: Loss Aversion in Riskless Choice: A Reference- Dependent Model. The Quarterly Journal of Economics 106(4), 1039–1061 (1991)
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)
Widz, S., Revett, K., Ślȩzak, D.: A Rough Set-Based Magnetic Resonance Imaging Partial Volume Detection System. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds.) PReMI 2005. LNCS, vol. 3776, pp. 756–761. Springer, Heidelberg (2005)
Widz, S., Slezak, D.: Approximation Degrees in Decision Reduct-Based MRI Segmentation. In: FBIT 2007: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies, pp. 431–436. IEEE Computer Society Press, Los Alamitos (2007)
Zak, P.J.: Neuroeconomics. Philosophical Transactions of the Royal Society of London, Series B, Biological Science 359(1451), 1737–1748 (2004)
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Kacprzyk, J. (2008). Neuroeconomics: Yet Another Field Where Rough Sets Can Be Useful?. In: Chan, CC., Grzymala-Busse, J.W., Ziarko, W.P. (eds) Rough Sets and Current Trends in Computing. RSCTC 2008. Lecture Notes in Computer Science(), vol 5306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88425-5_1
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DOI: https://doi.org/10.1007/978-3-540-88425-5_1
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