By Yuhsuke Koyama, Ko Ishiyama, Hiroyuki Kaneko, Isao Ono, Hiroyuki Matsui (auth.), Takao Terano Ph.D., Hajime Kita Dr. Eng., Hiroshi Deguchi Ph.D., Kyoichi Kijima Dr. Eng. (eds.)
Agent-Based Modeling/Simulation (ABM/ABS) is an rising box that permits bottom-up and experimental research in social sciences corresponding to economics, administration, sociology and politics. The chapters of this publication are the chosen papers from these awarded the 3rd foreign Workshop on Agent-Based ways in fiscal and Social advanced platforms held in Tokyo, Japan in 2005. Articles during this e-book covers methodological concerns, computational model/software, mixture with gaming simulation, and real-world functions to fiscal, management/organizational and social issues.
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Additional info for Agent-Based Approaches in Economic and Social Complex Systems IV: Post-Proceedings of The AESCS International Workshop 2005
Myerson and Sattertwaite (1983) Efficient Mechanisms for bilateral trading. Joumal of economic Theory 265-281 Osbome M. J, Rubinstein A (1990) Bargaining and Markets. Academic Press, San Diego, CA. Osbome M. J, Rubinstein A (1994) Bargaining and Markets. The MIT Press, Cambridge,MA. Rouchier J. (2004), Interactions routines and selfish behaviours in an artificial market, WEHIA 2004, Kyoto. Rouchier J. P (2004) Trade relation and moral link in transactions among retailers and wholesale sellers on the Amavaux market.
However, agents do not necessarily confine themselves with just stationary Markov processes. Actually, they can never be sure whether the underlying process will remain unchanged over time. So, they stay alert to that possibility, and keep on trying different Markov processes with different time frames (time horizons). Specifically, each belief can be described as "a fcth order Markov process appearing over the last d days and may continue". ^ Once the belief is determined, the low-level GA is applied to solve the stochastic dynamic optimization problem defined in (1) - (3).
T h e results are mixed, depending on how we approach this issue. While the s t a n d a r d analytic approach proves the irrelevance of risk preference to survivabihty (, ), the agent-based computational approach indicates the opposite (, ). This kind of inconsistency, as quite often seen in the agent-based computational economics literature, simply re- 42 Market and Policy fleets the sensitivity of the classical (analytical) results to the interacting heterogeneous boundedly-rational behavior.