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Transactions of the Institute of Systems, Control and Information Engineers Vol. 23 (2010), No. 10

ISIJ International
belloff
ONLINE ISSN: 2185-811X
PRINT ISSN: 1342-5668
Publisher: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

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  1. Vol. 37 (2024)

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  5. Vol. 33 (2020)

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  6. Vol. 32 (2019)

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  11. Vol. 27 (2014)

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  14. Vol. 24 (2011)

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  15. Vol. 23 (2010)

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  16. Vol. 22 (2009)

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  25. Vol. 13 (2000)

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  26. Vol. 12 (1999)

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  27. Vol. 11 (1998)

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  28. Vol. 10 (1997)

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  29. Vol. 9 (1996)

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  30. Vol. 8 (1995)

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  31. Vol. 7 (1994)

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  32. Vol. 6 (1993)

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  33. Vol. 5 (1992)

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  34. Vol. 4 (1991)

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  35. Vol. 3 (1990)

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  36. Vol. 2 (1989)

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  37. Vol. 1 (1988)

    1. No.7
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    5. No.3
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Keyword Ranking

21 Nov. (Last 30 Days)

Transactions of the Institute of Systems, Control and Information Engineers Vol. 23 (2010), No. 10

Multi-Agent Simulation for Choice under Risk

Ichiro Nishizaki, Tomohiro Hayashida

pp. 227-235

DOI:

10.5687/iscie.23.227

Abstract

In this paper, we develop a simulation system with artificial autonomous adaptive agents selecting one out of a given pair of binary lotteries which are represented by probability distributions over two outcomes. Agent’s decisions are made by a learning classifier system, and after classifying information of a given pair of binary lotteries, an agent chooses one out of them. The condition part of a classifier consists of conditions identifying probabilities and payoffs of a pair of binary lotteries and conditions identifying characteristics of the lotteries known by several models describing behavioral regularities of choices under risk. We compare the result of the simulation with that of the experiment by Selten et al. (1999), and demonstrating the similarity between them, we consider a mechanism of human choices under risk. Finally, we examine the possibility of controlling a subject’s preference with respect to risky events by the lottery ticket procedure.

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Multi-Agent Simulation for Choice under Risk

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Ris

Frequency Domain Identification Based on Particle Swarm Optimization

Takashi Wada, Toshiharu Sugie

pp. 236-242

DOI:

10.5687/iscie.23.236

Abstract

The paper proposes a frequency domain identification method for linear continuous-time systems including delay ones. The model parameters are estimated by minimizing the cost functions which are appropriate for open/closed loop. The minimization is achieved through Particle Swarm Optimization, which attracts a lot of attention recently in the evolutionary computation area due to its empirical evidence of its superiority. Its effectiveness is demonstrated by numerical examples. In addition, a comparison with the existing optimization method is given to show the robustness of the proposed method. Furthermore, an experimental evaluation using a magnetic levitation system is performed.

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Frequency Domain Identification Based on Particle Swarm Optimization

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Ris

Remarks on Asymptotic Property of Stabilization Problems Related to a Class of Networked Control

Kentaro Hirata

pp. 243-245

DOI:

10.5687/iscie.23.243
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Remarks on Asymptotic Property of Stabilization Problems Related to a Class of Networked Control

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On the Relationship between the Best Achievable Performances in the Sensitivity and Complementary Sensitivity Reduction Problems of Discrete-Time Systems

Yoshimichi Ito, Hiroshi Shirahama

pp. 246-248

DOI:

10.5687/iscie.23.246
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On the Relationship between the Best Achievable Performances in the Sensitivity and Complementary Sensitivity Reduction Problems of Discrete-Time Systems

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