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題名 隨機穩定性:一個新的演算方法及在隨機演化賽局中的應用
Stochastic Stability: Algorithmic Analysis
作者 劉吉商
Liu, Chi-Shang
貢獻者 莊委桐
Juang,Wei-Torng
劉吉商
Liu,Chi-Shang
關鍵詞 演化
突變
隨機穩定性
演算法
evolution
mutation
stochastic stability
basin of attractions
algorithm
日期 2007
上傳時間 6-May-2016 17:00:47 (UTC+8)
摘要 本篇論文研究演化的動態過程中的隨機穩定性。演化過程中,突變(mutation)或變異隨時可能會發生。因此,演化中不存在安定(steady)或是穩定(stable)的狀態。但是當突變機率趨近於零時,有些狀態在長期間比其他狀態容易出現在過程中為人所觀察到。這些狀態稱為隨機穩定狀態(stochastically stable state)。我們發展出一具有一般性的演算法來找出所有的隨機穩定狀態。有別於傳統演算法,這套演算法大幅降低計算所需次數。透過這套演算法,我們定義了一個集合: stable set。我們發現,stable set包涵了所有的隨機穩定狀態。同時,我們也提出數個隨機穩定狀態的充份條件。這些發現代表著,分析演化模型的假設及均衡(equilibria)性質之間的關係是可行的。
We study the behaviors of the evolutionary models with persistant noises through a general algorithm which describes the relationships among the stochastic potentials. That is, by constructing a closed loop on the graph of the directed trees, we show that the comparison among the stochastic potential is equivalent to the comparison among one-step transition costs. Hence, we are able to systematically analyze the properties of the stochastically stable states. Our main nding is that the set of the stochastically stable states is contained in a set, which we dene as a stable set. Each state in this set is difcult to escape from and is resistant to the attraction of any other states in the stable set. Based on this nding, related sufficient conditions for the stochastically stable states are presented, and some results
     in the literature are also reinterpreted. In addition, we show that this algorithm drastically reduces the necessary steps for characterizing the stochastically stable states.
     This means that the analysis on relationships between the assumptions of the model and the properties of equilibria are possible and promising.
參考文獻 [1] Ellison, G. (2000), “Basin of attraction, long run stochastic stability and the speed of
     step-by-step evolution”, Review of Economic Studies, 67, 17-45
     [2] Freidlin, M. I. and A. D. Wentzell (1984), Random Perturbations of Dynamical Systems,
     New York: Spring Verlag.
     [3] Friedman, J. and C. Mezzetti (2001), “Learning in Games by Random Sampling”, Jour-
     nal of Economic Theory, 98, 55-84
     [4] Kandori, M., G. J. Mailath and R. Rob (1993), “Learning, mutation, and long run
     equilibrium in games”, Econometrica, 61, 29-56
     [5] Kandori, M. and R. Rob (1995), “Evolution of equilibria in the long run: a general
     theory and applications”, Journal of Economic Theory, 65, 383-414
     [6] Kandori, M. and R. Rob (1998), “Bandwagon e¤ects and long run technology choice”,
     Games and Economic Behavior, 22, 30-60
     [7] Samuelson, L (1994), “Stochastic stability in games with alternative best reply”, Journal
     of Economic Theory, 64, 35-65
     63
     [8] Maruta, Toshimasa (1997), “On the relationships between risk dominance and stochastic
     stability”, Games and Economic Behavior, 19, 221-234
     [9] Vannetelbosch, Vincent J. and Tercieux Olivier (2005), “A Characterization of Stochas-
     tically Stable Networks“, FEEM Working Paper No. 48.05.
     [10] Robson, A.J. and F. Vega-Redondo (1996), “E¢ cient equilibrium selection in evolution-
     ary games with random matching”, Journal of Economic Theory, 70, 65-92
     [11] Vega-Redondo, F. (2003), Economics and the Theory of Games, Cambridge: MIT P
描述 碩士
國立政治大學
經濟學系
92258030
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0922580302
資料類型 thesis
dc.contributor.advisor 莊委桐zh_TW
dc.contributor.advisor Juang,Wei-Torngen_US
dc.contributor.author (Authors) 劉吉商zh_TW
dc.contributor.author (Authors) Liu,Chi-Shangen_US
dc.creator (作者) 劉吉商zh_TW
dc.creator (作者) Liu, Chi-Shangen_US
dc.date (日期) 2007en_US
dc.date.accessioned 6-May-2016 17:00:47 (UTC+8)-
dc.date.available 6-May-2016 17:00:47 (UTC+8)-
dc.date.issued (上傳時間) 6-May-2016 17:00:47 (UTC+8)-
dc.identifier (Other Identifiers) G0922580302en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/94562-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 92258030zh_TW
dc.description.abstract (摘要) 本篇論文研究演化的動態過程中的隨機穩定性。演化過程中,突變(mutation)或變異隨時可能會發生。因此,演化中不存在安定(steady)或是穩定(stable)的狀態。但是當突變機率趨近於零時,有些狀態在長期間比其他狀態容易出現在過程中為人所觀察到。這些狀態稱為隨機穩定狀態(stochastically stable state)。我們發展出一具有一般性的演算法來找出所有的隨機穩定狀態。有別於傳統演算法,這套演算法大幅降低計算所需次數。透過這套演算法,我們定義了一個集合: stable set。我們發現,stable set包涵了所有的隨機穩定狀態。同時,我們也提出數個隨機穩定狀態的充份條件。這些發現代表著,分析演化模型的假設及均衡(equilibria)性質之間的關係是可行的。zh_TW
dc.description.abstract (摘要) We study the behaviors of the evolutionary models with persistant noises through a general algorithm which describes the relationships among the stochastic potentials. That is, by constructing a closed loop on the graph of the directed trees, we show that the comparison among the stochastic potential is equivalent to the comparison among one-step transition costs. Hence, we are able to systematically analyze the properties of the stochastically stable states. Our main nding is that the set of the stochastically stable states is contained in a set, which we dene as a stable set. Each state in this set is difcult to escape from and is resistant to the attraction of any other states in the stable set. Based on this nding, related sufficient conditions for the stochastically stable states are presented, and some results
     in the literature are also reinterpreted. In addition, we show that this algorithm drastically reduces the necessary steps for characterizing the stochastically stable states.
     This means that the analysis on relationships between the assumptions of the model and the properties of equilibria are possible and promising.
en_US
dc.description.tableofcontents 1.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
     2.0 CANONICAL EVOLUTIONARY MODEL . . . . . . . . . . . . . . . . . 7
     2.1 The Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
     2.2 Limit distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
     2.3 The Identi…cation of the Stochastically Stable State . . . . . . . . . . . . . . 11
     3.0 STOCHASTIC STABILITY: ALGORITHM AND ANALYSIS . . . . . 17
     3.1 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
     3.2 Stochastic Stability: Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 36
     3.2.1 Stable Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
     3.2.2 Some Su¢ cient Conditions for the Stochastically Stable States . . . . 41
     3.3 Relationships with the Approaches in Literatures . . . . . . . . . . . . . . . 50
     3.3.1 Ellison’s Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
     v
     3.3.2 Young’s approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
     4.0 CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
     BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0922580302en_US
dc.subject (關鍵詞) 演化zh_TW
dc.subject (關鍵詞) 突變zh_TW
dc.subject (關鍵詞) 隨機穩定性zh_TW
dc.subject (關鍵詞) 演算法zh_TW
dc.subject (關鍵詞) evolutionen_US
dc.subject (關鍵詞) mutationen_US
dc.subject (關鍵詞) stochastic stabilityen_US
dc.subject (關鍵詞) basin of attractionsen_US
dc.subject (關鍵詞) algorithmen_US
dc.title (題名) 隨機穩定性:一個新的演算方法及在隨機演化賽局中的應用zh_TW
dc.title (題名) Stochastic Stability: Algorithmic Analysisen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] Ellison, G. (2000), “Basin of attraction, long run stochastic stability and the speed of
     step-by-step evolution”, Review of Economic Studies, 67, 17-45
     [2] Freidlin, M. I. and A. D. Wentzell (1984), Random Perturbations of Dynamical Systems,
     New York: Spring Verlag.
     [3] Friedman, J. and C. Mezzetti (2001), “Learning in Games by Random Sampling”, Jour-
     nal of Economic Theory, 98, 55-84
     [4] Kandori, M., G. J. Mailath and R. Rob (1993), “Learning, mutation, and long run
     equilibrium in games”, Econometrica, 61, 29-56
     [5] Kandori, M. and R. Rob (1995), “Evolution of equilibria in the long run: a general
     theory and applications”, Journal of Economic Theory, 65, 383-414
     [6] Kandori, M. and R. Rob (1998), “Bandwagon e¤ects and long run technology choice”,
     Games and Economic Behavior, 22, 30-60
     [7] Samuelson, L (1994), “Stochastic stability in games with alternative best reply”, Journal
     of Economic Theory, 64, 35-65
     63
     [8] Maruta, Toshimasa (1997), “On the relationships between risk dominance and stochastic
     stability”, Games and Economic Behavior, 19, 221-234
     [9] Vannetelbosch, Vincent J. and Tercieux Olivier (2005), “A Characterization of Stochas-
     tically Stable Networks“, FEEM Working Paper No. 48.05.
     [10] Robson, A.J. and F. Vega-Redondo (1996), “E¢ cient equilibrium selection in evolution-
     ary games with random matching”, Journal of Economic Theory, 70, 65-92
     [11] Vega-Redondo, F. (2003), Economics and the Theory of Games, Cambridge: MIT P
zh_TW