Advancing the state of the art of simulation in the social sciences requires appreciating the unique value of simulation as a third way of doing science, in contrast to both induction and deduction. Simulation can be an effective tool for discovering surprising consequences of simple assumptions. This essay offers advice for doing simulation research, focusing on the programming of a simulation model, analyzing the results and sharing the results with others. Replicating other people’s simulations gets special emphasis, with examples of the procedures and difficulties involved in the process of replication. Finally, suggestions are offered for fostering of a community of social scientists who do simulation.

This paper deals with the synthesis of multi-agent systems based on the co-evolutionary Genetic Programming (GP) by considering social learning and its applications to the analysis of artificial stock markets. Cognitive behaviors of agents are modeled by using the GP to introduce social learning as well as individual learning. Assuming five types of agents, which rational agents prefer forecast models (equations) or production rules to support their decision making, and irrational agents select decisions at random like a speculation. Rational agents usually use their own knowledge base, but some of them utilize their public (common) knowledge base to improve trading decisions. By using the result of simulation studies on artificial market, it is shown that the time series for stock price is resemble to real stock price statistically, then the effectiveness of the scheme in the paper is proved.

Because the competitive advantage position for a company is able to realize by the investment to the business system of its own, the framework of an investment strategy becomes the foundation of competitive strategy. The analytical framework proposed by M.E.Porter is popular among business managers because of usefulness under the real competitive environment. However, his framework is limited for the adaptation for it is descriptive and normative model.

So we developed the computer simulator based on the agent approach that made the decision making of business managers support.

The characteristic of this system is the following 3 points. First we considerate that the system is able to be adapted various industries and to make various simulations under the conditions changed by user freely. Secondly, we realize the multi-agents system that has an investment policy based on agent’s own knowledge level, for framework of an investment has various options generally.

This paper discusses the effectiveness of sharing information concerning the reputation of buyers and sellers in an online C2C market. We developed a computer simulation model, which describes online transactions with a reputation information management system to share information concerning the reputation of consumers. It is designed on an agent-based approach specifically iterated prisoners dilemma game theory. According to the results of a simulation, a positive reputation system can be more effective than a negative reputation system for an online transaction. The results should be an important suggestion for designing a reputation system of online transaction.

To discuss effective ways for preventing organizational accidents based on systems thinking, this paper first develops an agent-based simulation model for describing incident report transmission process within an organization. We then derive some insighs about relationship between the accidents and

organizational culture from our experimental results.

Recently, we have had a lot of “organizational accidents”. Organizational accidents are accidents due to such corporate structure that puts efficiency ahead of safety. J. T. Reason claims that safety culture is necessary to prevent such organizational accidents. According to him, safety culture is essentially based on an informed culture that has four subcomponents; a reporting culture , a just culture, a flexible culture and a learning culture. We try to investigate such features of informed culture by using a simulation model.

In this paper, we work on the technological competition in high-tech industries. Industrial polices are a very import to encourage technological innovation. Trading policies is also very important if there exist foreign market. Guard the interests of the developer through patent is important to spur technological innovations. However some open source project is helpful to develop software rapidly because the developers can imitate their technology each other. We verify the effect of industrial policies, trading policies, and patent policy in our virtual high-tech industry. We formulate a multi-agent model of virtual high-tech industry by agent-based simulation. We assumed three different types of firm agents in our virtual societies, in which each different agent has a different goal. We discuss the resource allocation of investment. R&D investment affects the quality of goods; capital investment affects the quantity of goods in our model.