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Multiagent simulation and individual's adaptive behaviors in resource shortage

ZHAO Chun jun, HUA Li School of Economics and Management, Tsinghua University, Beijing 100084  
Theories of information economics and multiagent system are adopted as analysis frame for this paper, with Swarm as the simulation tool. Swarm is a software package for multiagent simulation of complex systems being developed at the Santa Fe Institute, which has been a useful tool for researchers in a variety of disciplines, especially artificial life. In this paper we use it to describe agents' selection, competition, and adaptive behaviors in resource shortage, and the evolution of institutions as a whole. Agents interact each other by local information and relatively simple reinforcement algorithms, and new data are collected from the environment and processed, which change the internal model of the agent in the end. Research evinces that simple adaptive behaviors of individuals can lead to complex system characteristics in higher level. Agent learns a lot from analysis of the operation history and by communications among them. New institution emerges in some conditions, which is often quite efficient in the context.Furthermore, we observe that complex system behaviors such as moral hazard and reverse selection may evolve out due to informational asymmetries. This research helps to explain the universal occupation phenomenon in real world, and the evolution of property right and institutions. Above all, multiagent simulation used in this paper offered a quite new perspective in research of complex social economic phenomena.
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