Download Agent-Based Modeling Meets Gaming Simulation by Hiroshi Deguchi (auth.), Kiyoshi Arai D.Eng., Hiroshi PDF

By Hiroshi Deguchi (auth.), Kiyoshi Arai D.Eng., Hiroshi Deguchi D.Sc, D.Econ., Hiroyuki Matsui D.Eng. (eds.)

This number of first-class papers cultivates a brand new viewpoint on agent-based social process sciences, gaming simulation, and their hybridization. lots of the papers incorporated right here have been awarded within the specific consultation titled Agent-Based Modeling Meets Gaming Simulation at ISAGA2003, the thirty fourth annual convention of the foreign Simulation and Gaming organization (ISAGA) at Kazusa Akademia Park in Kisarazu, Chiba, Japan, August 25–29, 2003. This post-proceedings used to be supported via the twenty-?rst century COE (Centers of Excellence) application production of Agent-Based Social platforms Sciences (ABSSS), confirmed on the Tokyo Institute of know-how in 2004. the current quantity contains papers submitted to the exact consultation of ISAGA2003 and offers an excellent instance of the varied scope and conventional of analysis completed in simulation and gaming this present day. The subject of the designated consultation at ISAGA2003 was once Agent-Based Modeling Meets Gaming Simulation. these days, agent-based simulation is changing into extremely popular for modeling and fixing advanced social phenomena. it's also used to reach at sensible options to social difficulties. whilst, although, the validity of simulation doesn't exist within the magni?cence of the version. R. Axelrod stresses the simplicity of the agent-based simulation version in the course of the “Keep it easy, silly” (KISS) precept: As a terrific, easy modeling is essential.

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In: Terano T, Deguchi H, Takadama K (eds) Meeting the challenge of social problems via agentbased simulation. IOS, (Amsterdam) pp 167–178 Taniguchi K, Nakajima Y, Hashimoto F (2004) A report of U-Mart experiments by human agents. In: Shiratori R, Arai K, Kato F (eds) Gaming, simulations, and society research scope and perspective. Springer, Berlin Heidelberg New York Tokyo, pp 49–57 U-Mart Project (2005) U-Mart Project. org/, cited 1 Apr 2005 The Gaming of Firm Strategy in High-Tech Industry: Human Agents and Artificial Intelligence Agents Intermingled in a Simulation Model Hao Lee1 and Hiroshi Deguchi2 Introduction Research and development (R&D) activity is vitally important to modern industry and any firm that leads the research field in new technology will naturally increase its chances of financial success in the marketplace.

2: Qi , t = FPi , t C (2) Ti,t represents the technological level of firm i for previous term t − 1. T−i,t−1 represents the technological level of firms other than firm i for term t. T is the technological innovation function. The technological level of a firm is defined in Eq. 3: Ti , t = T ( FRi , t , Ti , t −1 , T− i , t −1 ) (3) The product price for firm i for term t is Pi,t, which is defined in Eq. 4. T−i,t shows the technological level of firms other than firm i on term t. Q−i,t represents the sum of the production quantities of firms other than firm i for term t.

There are also two actions in a classifier. The percentage of production investment is the first action and is represented by Cx. The percentage of R&D investment is the second action and is represented by Dx. { Rule 1: ( A 1 , B1 , C1 , D1 , Wp1 , Ws1 , Wt1 ) Rule x: ( A x , Bx , C x , Dx , Wp x , Ws x , Wt x ) Rule m: ( A m , Bm , C m , Dm , Wp m , Ws m , Wt m )} (10) The R&D investment, the firm’s past technological level, and the average technological level in the industry prescribe the limits of technological development for the firm.

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