New PDF release: Agent-Based Modeling Meets Gaming Simulation (Agent-Based

By Kiyoshi Arai, Hiroshi Deguchi, Hiroyuki Matsui

ISBN-10: 4431294260

ISBN-13: 9784431294269

This choice of very good papers cultivates a brand new point of view on agent-based social approach sciences, gaming simulation, and their hybridization. lots of the papers incorporated the following have been provided within the targeted 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 options to social difficulties. whilst, even if, 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 incredible, basic modeling is essential.

Many real social phenomena are extra complicated than might be defined via the easy modeling precept, although. we have to build a version of complicated phenomena as a reproduction of a true state of affairs. it's tough to mix truth and sim- plicity in a version, specifically while the phenomena comprise many brokers as selection 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 avid 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)

Sample text

State/action/reward encoding for XCS learning agent State Round number Demand prediction Material stock Last action Last 2 action 4 bit 8 bit 6 bit 5 bit 5 bit 1–10 0–255 000 (unit 1 000) 0–6 300 (unit 100) “Action” info below “Action” info below Action Sales price Product order Material order 1 bit 1 bit 3 bit Min/max Yes/no 0–2 100 (unit 300) Reward Cash amount int Game result + offset 54 M. Kobayashi and T. Terano Table 2. XCS Parameter setting for the experiments Parameters in XCS Max population numbers Learning ratio Fitness parameters on CF Accuracy Discount ratio of pred.

It is very difficult to design a model that combines the complexity to imitate real markets and the simplicity to allow computational experiments to be conducted, and 3. Researchers need to share common understanding on experimental configuration and results that are much more complicated than those of conventional theoretical models. U-Mart [3,4] is a research program that provides a method for the study of artificial markets. The program builds an artificial market simulation system as a test bed for economists and computer scientists to conduct studies through shared understanding.

Matsui et al. Analysis Tools Courseware Research Textbook Researchers Machine Agent GUI tools Data Developing tools Researcher Rules, Regulations Data Targets Motivation, GUI tools Education Developing tools Events Participants (Machine and Human Agents) Fig. 2. Activities of U-Mart Project. GUI, Graphical user interface financial market system. To be more specific, we are trying to establish methods of market manipulation by circuit breakers such as commission rate and price movement limits, as well as by controlling the degree and scope of information release, such as the existence of market makers, calculation methods for the indicative price, and change of update intervals.

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Agent-Based Modeling Meets Gaming Simulation (Agent-Based Social Systems, Volume 2) by Kiyoshi Arai, Hiroshi Deguchi, Hiroyuki Matsui


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