Download e-book for kindle: Agent-Based Approaches in Economic and Social Complex by Yusuke Goto, Shingo Takahashi (auth.), Tadahiko Murata,

By Yusuke Goto, Shingo Takahashi (auth.), Tadahiko Murata, Takao Terano, Shingo Takahashi (eds.)

ISBN-10: 4431542787

ISBN-13: 9784431542780

ISBN-10: 4431542795

ISBN-13: 9784431542797

Agent-based modeling/simulation is an emergent method of the research of social and monetary platforms. It presents a bottom-up experimental strategy to be utilized to social sciences akin to economics, administration, sociology, and politics in addition to a few engineering fields facing social actions. This publication comprises chosen papers provided on the 7th foreign Workshop on Agent-Based methods in fiscal and Social advanced platforms held in Osaka, Japan, in 2012.

At the workshop, 24 reviewed complete papers have been offered, and of these, 17 have been chosen to be incorporated during this quantity. The papers are divided into teams as "Fundamentals of Agent-Based Modeling" and "Applications of Agent-Based Modeling".

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Additional info for Agent-Based Approaches in Economic and Social Complex Systems VII: Post-Proceedings of The AESCS International Workshop 2012

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Lam TK (1992) Aspiration level adaption: an empirical exploration. Manag Sci 38:623–644 4. Levinthal D, March JG (1981) A model of adaptive organizational search. J Econ Behav Org 2:307–333 5. Levinthal DA, March JG (1993) The myopia of learning. Strateg Manag J 14:95–112 6. March JG (1991) Exploration and exploitation in organizational learning. Org Sci 2:71–87 7. March J (1996) Continuity and change in theories of organizational action. Adm Sci Q 41: 278–287 8. Simon HA (1991) Bounded rationality and organizational learning.

In March’s model, he uses a parameter in terms of probability that reflects the effectiveness 24 M. Siallagan et al. Fig. , learning from the code (p1 ). In this research, we use the probability of learning from the code of individuals to determine the effectiveness of socialization. 7 Updating the Aspiration Level At the end of each time step, the individuals interact with each other to share their aspiration level. Each individual interacts randomly at all times. Let αi (t) be a level of sharing aspiration for individual i at time t, and let Ti be a set of individuals who interact with individual i.

References 1. Axelrod R (1986) An evolutionary approach to norms. Am Polit Sci Rev 80:1095–1111 2. Carley KM, Svoboda DM (1996) Modeling organizational adaptation as a simulated, annealing process. Sociol Methods Res 25:138–168 Agent-Based Simulation of Diversity and Organizational Performance 43 3. Chang M-H, Harrington JE (2000) Centralization vs. decentralization in a multi-unit organization: a computational model of a retail chain as a multi-agent adaptive system. Manag Sci 46:1427–1440 4. Chang M-H, Harrington JE (2003) Multi-market competition, consumer search, and the organizational structure of multi-unit firms.

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Agent-Based Approaches in Economic and Social Complex Systems VII: Post-Proceedings of The AESCS International Workshop 2012 by Yusuke Goto, Shingo Takahashi (auth.), Tadahiko Murata, Takao Terano, Shingo Takahashi (eds.)


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