By Kiyoshi Arai, Hiroshi Deguchi, Hiroyuki Matsui

This selection of first-class papers cultivates a brand new viewpoint on agent-based social method sciences, gaming simulation, and their hybridization. lots of the papers incorporated the following have been awarded within the detailed consultation titled Agent-Based Modeling Meets Gaming Simulation at ISAGA2003, the thirty fourth annual convention of the overseas Simulation and Gaming organization (ISAGA) at Kazusa Akademia Park in Kisarazu, Chiba, Japan, August 25–29, 2003.

Nowadays, agent-based simulation is turning into highly regarded for modeling and fixing complicated social phenomena. it's also used to reach at useful suggestions to social difficulties. even as, notwithstanding, the validity of simulation doesn't exist within the beauty of the version. R. Axelrod stresses the simplicity of the agent-based simulation version throughout the “Keep it basic, stupid” (KISS) precept: As an amazing, easy modeling is essential.

Many real social phenomena are extra advanced than might be defined by means of the easy modeling precept, notwithstanding. we have to build a version of complicated phenomena as a duplicate of a true state of affairs. it truly is tough to mix truth and sim- plicity in a version, in particular while the phenomena comprise many brokers as determination makers. How do we make the 2 diverse modeling rules compatible?

Gaming and simulation bargains a solution. If a human participant can perform a simulation version as a player–agent, then he can simply realize the truth of the version. Hybrid simulation makes attainable the hybridization of gaming simulation and agent-based simulation in a version. In a hybrid simulation, version human gamers and computer brokers simulate (play) the version even as.

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Extra info for Agent-Based Modeling Meets Gaming Simulation (Agent-Based Social Systems, Volume 2)

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Garbage can: a committee’s decisions are made when the sum of the participant’s inputted energy exceeds the amount of energy required to make the decisions needed to solve the problems. ” Fig. 1. Explanation example of participant, problem, and committee (garbage can) in the garbage can model 42 T. Kaneda and Y. Hattori 2. Fluttering problems: each problem is thrown into one committee in each term, and under the constraints of the given access structure it moves to another committee, which is best equipped to solve the problem.

Pi , t = P (Ti , t , T− i , t , Qi , t , Q− i , t ) (4) The Gaming of Firm Strategy in High-Tech Industry 33 The profit of firm i for term t is represented by Ri,t. The funds for the next term (t + 1) are represented by Fi,t+1, which is defined in Eq. 5: Fi , t +1 = Fi , t + Ri , t (5) We rewrite Fi,t+1 in Eq. 6 from the definition. Fi , t +1 = Pi , t × Qi , t (6) In this model, firms seeking profit maximization will maximize Ri,t and their goal is defined in Eq. 7. Firms seeking market share maximization will maximize Qi,t and their goal is defined in Eq.

In particular, this system is very handy as a platform for gaming simulation with scalability and usage in various experiments. In addition, the U-Mart system continuously grows as a system that can serve as a test bed for education and research. The more detailed information of the U-Mart Project can be obtained from the web site [8]. It is hoped that many people will take an interest and take part in the U-Mart project and the system will be used even more actively. Acknowledgments. The preparation of this chapter would have been impossible without the assistance of other participants in the U-Mart project.

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