A Novel Developments in Incentive Stackelberg Strategy for Positive systems
| Project/Area Number |
17K00034
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Mathematical informatics
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| Research Institution | Hiroshima University |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | インセンティブシュタッケルベルグゲーム / 非負システム / 確率システム / パレート準最適性 / ナッシュ均衡戦略 / SIRモデル / 凸最適化 / 繰り返し計算 / パレート最適戦略 / H∞制御 / 分散制御 / 非線形非負システム / 誘因戦略 / 線形行列不等式 / 情報基礎 / 数理工学 / 制御工学 |
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| Outline of Final Research Achievements |
The decision making problem based on the incentive Stackelberg game for a class of stochastic positive system was dealt with. First, a multi-player stochastic nonlinear positive system model governed by Ito's stochastic differential equation has been proposed by considering the stochastic noise that can represent the environmental fluctuations and deterministic input disturbance that can represent modeling error. Then, we have succeeded in designing the equilibrium strategy of the incentive Stackelberg game by H∞ control theory. In addition, Pareto suboptimality strategy and Nash equilibrium strategy were used for comparison in the lower layer. In the sequel, the static output feedback strategy set was addressed. As a result, it has been shown that it was possible to induce the follower in the lower layer to the desired equilibrium point in terms of the strategy of the leader in the upper layer with a constrained state information.
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| Academic Significance and Societal Importance of the Research Achievements |
提案された戦略設計手法は，従来にある2点境界値問題を解く必要がない．また，凸最適化手法を基盤とする線形行列不等式による繰返し数値計算アルゴリズムによって，容易に戦略設計が可能である．さらに，実際の非負システムへ適用するため，不確定要素を考慮した確率システムに対する戦略設計を提案した．特に，実用性を示すために，非負システムにおける重要な課題として知られるSIR感染モデルでのワクチン接種戦略決定を扱った．その結果，数値戦略解を得ることに成功した．これは，感染者人口の現時刻情報に基づく局所的な状態値のみによって，ワクチン接種戦略設計が行える点で，理論的かつ非常に実用的な結果である考えられる．
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Report
(4 results)
Research Products
(13 results)
