Development and Feature Extract of Strategy Acquisition Algorithm for Large-Scale Stochastic Field
Project/Area Number |
23500017
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Fundamental theory of informatics
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Research Institution | Hiroshima University |
Principal Investigator |
MUKAIDANI Hiroaki 広島大学, 工学(系)研究科(研究院), 教授 (70305788)
|
Co-Investigator(Kenkyū-buntansha) |
XU Hua 筑波大学, ビジネス科学研究科, 教授 (40253025)
|
Project Period (FY) |
2011 – 2013
|
Project Status |
Completed (Fiscal Year 2013)
|
Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
Keywords | ナッシュゲーム / パレート最適性 / 確率微分方程式 / マルコフジャンプシステム / 数値計算アルゴリズム / Nash equilibrium / Pareto optimality / Stackelberg game / Stochastic systems / Markov jump systems / Numerical algorithm / Romania / Australia |
Research Abstract |
In this study, Nash equilibrium strategy for a class of Markov jump stochastic systems is solved by using Ito stochastic differential equation. It is worth pointing out that Markov jump stochastic systems can represent the model variation and disturbance for large-scale systems. That is, computational algorithms for obtaining a robust stochastic strategy set against the abruptly changing parameters such as the power failure are developed. It is shown that the proposed Nash strategy attain the stochastic equilibrium and the optimality.
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Report
(4 results)
Research Products
(34 results)