Download Agent-Based Approaches in Economic and Social Complex by T. Terano, H. Kita, H. Deguchi, K. Kijima PDF

By T. Terano, H. Kita, H. Deguchi, K. Kijima

The chapters of this e-book are the chosen papers from these provided on the 3rd foreign Workshop on Agent-Based ways in fiscal and Social complicated structures held in Tokyo, Japan in 2005. Articles disguise methodological matters, computational model/software, mixture with gaming simulation, and real-world purposes to monetary, management/organizational and social matters.

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Our interest is unusual, since we want to focus on the nature of interactions and the evolution of the bargaining power, the elements that are as important as the evolution of prices. In that sense, the model reproduces rather well the empirical data, given parameters. The general result is that, in any case, initial values of beliefs and reservation values have little, if no, influence on prices and or the loyalty of buyers. This first stage of calibration and test of sensitivity to parameters was hence, fundamental.

12. Holland J, Miller J (1991) Artificial Adaptive Agents in Economic Theory. American Economic Review 81 (2): 365-370. 13. Jorion P, Giovannini A (1993) Time Series Tests of a Non-expected-Utility Model of Asset Pricing. European Economic Review 37: 1083-1100. 14. Kandel S, Stambaugh R-F (1991) Asset Returns and Intertemporal Preferences. Journal of Monetary Economics 27: 39-71. 15. Lucas D (1994) Asset Pricing with Undiversifiable Risk and Short Sales Constraints: Deepening the Equity Premium Puzzle.

The learning objectives of this tool are to: 1) analyze the decision-makings from the succeeded (or failed) patterns of the case, and 2) plan the own decision-makings through the actual decision-makings in the games and the analyses of the results. The original BMDS requires a facilitator who manages the process of the game. We have ameliorated the BMDS to allow a learner to proceed with the game without a facilitator so that the learner is able to study by oneself. We have pre-determined the other players' behaviors by describing the agents.

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