By Robert L. Axtell (auth.), Takao Terano Ph.D., Hiroshi Deguchi Ph.D., Keiki Takadama Ph.D. (eds.)
The sequence of foreign workshops on Agent-Based methods in fiscal and Social advanced platforms (AESCS) is a part of the global actions on computational social and organizational sciences. the second one workshop, AESCS ’02, concentrating on growth of agent-based simulation was once held in Tokyo in August 2002. AESCS ’02 explored the frontiers of the sphere. the significance of cumulative development was once emphasised in discussions of universal projects, normal computational versions, replication and validation matters, and review and verification standards. selling multidisciplinary paintings in computational economics, organizational technology, social dynamics, and intricate structures, AESCS ’02 introduced jointly researchers from varied fields. This ebook comprises the invited papers through Robert Axtell, Shu-Heng Chen, and Takao Terano, in addition to chosen papers gathered in 3 significant sections: monetary platforms, advertising and marketing and administration, and Social structures and technique.
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Otherwise, a firm seeking technological level maximization slants toward R&D 30 H. Lee and H. Deguchi investment. A finn seeking profit maximization has the investment tendency which keeps a balance between R&D investment and production capacity investment. Besides, a finn seeking profit maximization is sensitive to environmental changes and thereby switches its strategy frequently. A finn seeking share maximization is not very interested in product quality of other firms . Finns seeking technological level maximization are not very interested in the production of other firms, However, firms seeking profit maximization cannot select the best strategy if they do not always detect the action of other firms .
Accordingly, it is reasonable to represent the heterogeneity of an agent by some probability density functions and to regard rational or irrational decisions as stochastic variables. Lastly, many social systems can be represented by graphs in which agents are expressed by nodes and the relationships between agents are symbolized by edges. Recently, the study of networks has attracted the attention of many scientists (Watts 1999; Barabasi 2002; Strogatz 2001; Albert and Barabasi 2002), and it has become clear that many real-world networks can be understood as small-world networks (Watts and Strogatz 1998) and scale-free networks (Albert et al.
In: Takayasu H (ed) Empirical science of financial fluctuations: The advent of econophysics. Springer-Verlag, Tokyo, pp . 343-352 Souma W , et al (2001c) Small-world effects in wealth distribution . arXiv:condmat/0108482 Souma W, et al (2002) Complex networks and economics . Proc Int Econ Conf, to be published in Physica A Strogatz SH (2001) Exploring complex networks. Nature 410:268-276 Takayasu H, et al (1997) Stable infinite variance fluctuations in randomly amplified Langevin systems. Phys Rev Lett 79:966-969 Watts DJ (1999) Small worlds: The dynamics of networks between order and randomness.