Strategy dynamics, decision making, and global performance in agent-based models of competing populations.
Chan King Pak Keven = 競爭性系統個體模型中的策略動態、決策及整體表現 / 陳景柏. === Thesis submitted in: August 2005. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. === Includes bibliographical references (leaves vii-viii (4th gp.)). === Text in English; abstracts in English and Chinese. === Chan King Pak Keven...
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Online Access: | http://library.cuhk.edu.hk/record=b5896477 http://repository.lib.cuhk.edu.hk/en/item/cuhk-325528 |
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Statistical physics Game theory |
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Statistical physics Game theory Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
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Chan King Pak Keven = 競爭性系統個體模型中的策略動態、決策及整體表現 / 陳景柏. === Thesis submitted in: August 2005. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. === Includes bibliographical references (leaves vii-viii (4th gp.)). === Text in English; abstracts in English and Chinese. === Chan King Pak Keven = Jing zheng xing xi tong ge ti mo xing zhong de ce lüe dong tai, jue ce ji zheng ti biao xian / Chen Jingbo. === Chapter 1 --- Introduction --- p.1 === Chapter 2 --- Review on the Minority Game --- p.5 === Chapter 2.1 --- Background --- p.5 === Chapter 2.2 --- Model of MG --- p.6 === Chapter 2.3 --- Features --- p.7 === Chapter 2.3.1 --- Phase Transition --- p.7 === Chapter 2.3.2 --- Inefficient and Efficient Phase --- p.8 === Chapter 2.3.3 --- Anti-persistence --- p.9 === Chapter 2.3.4 --- Data Collapse --- p.10 === Chapter 2.4 --- Existing Theories --- p.10 === Chapter 2.4.1 --- Reduced Strategy Space --- p.11 === Chapter 2.4.2 --- The Crowd-Anticrowd Theory --- p.12 === Chapter 2.5 --- Summary --- p.13 === Chapter 3 --- Introduction to Strategy Ranking Theory --- p.15 === Chapter 3.1 --- Strategy Ranking Theory for Mean Success Rate --- p.15 === Chapter 3.1.1 --- Time evolution of Virtual Point Ranking --- p.15 === Chapter 3.1.2 --- Winning Probability for m = 1 --- p.17 === Chapter 3.2 --- Calculation of Mean Success Rate --- p.21 === Chapter 3.3 --- "Size Dependence of weυen(K) (""Market Impact"" Effect)" --- p.23 === Chapter 3.4 --- Size Dependence of wodd、K) (Uneven Distribution of Agents into Split Ranks) --- p.25 === Chapter 4 --- Implementation of Strategy Ranking Theory --- p.30 === Chapter 4.1 --- Feature of wodd(k) for higher m --- p.30 === Chapter 4.2 --- Derivation of wodd(k) from Strategy Ranking Theory --- p.32 === Chapter 4.3 --- Proof of Eq. (4.14) --- p.36 === Chapter 4.4 --- Discussion on wodd(k) --- p.41 === Chapter 4.4.1 --- Asymptotic Behavior of wodd(k) --- p.42 === Chapter 4.4.2 --- Finite size correction of wodd(k) --- p.43 === Chapter 5 --- Applications of Strategy Ranking Theory --- p.46 === Chapter 5.1 --- Probability Density Function of Agents Making a Particular Choice --- p.46 === Chapter 5.1.1 --- Odd time steps: k = 1 --- p.47 === Chapter 5.1.2 --- Odd time steps: k = 2 --- p.48 === Chapter 5.1.3 --- "Rodd,K" --- p.49 === Chapter 5.1.4 --- Even time steps --- p.51 === Chapter 5.1.5 --- Overall Attendance Distribution --- p.51 === Chapter 5.2 --- The Variance of the Attendance --- p.52 === Chapter 5.2.1 --- Asymptotic behavior of the variance --- p.54 === Chapter 5.3 --- Anti-persistent Nature of Efficient Phase of MG --- p.55 === Chapter 5.4 --- Summary --- p.58 === Chapter 6 --- Strategy Ranking Theory and Crowd-Anticrowd Theory --- p.59 === Chapter 6.1 --- Introduction --- p.59 === Chapter 6.1.1 --- Strategy Ranking Theory --- p.60 === Chapter 6.1.2 --- Crowd-Anticrowd Theory --- p.61 === Chapter 6.2 --- Crowd-Anticrowd Theory with Ranking Patterns Characterized by k --- p.63 === Chapter 6.3 --- Variance: Crowd-Anticrowd Theory --- p.65 === Chapter 6.3.1 --- m = 1 --- p.65 === Chapter 6.3.2 --- m = 2 --- p.66 === Chapter 6.4 --- Variance: Modified Crowd-Anticrowd Theory for m̐ơح 1 --- p.66 === Chapter 6.4.1 --- k = 0 --- p.67 === Chapter 6.4.2 --- k = 1 --- p.67 === Chapter 6.4.3 --- k = 2 --- p.67 === Chapter 6.4.4 --- Sum over all k --- p.68 === Chapter 6.5 --- Variance: Modified Crowd-Ant icrowd Theory for m=2 --- p.68 === Chapter 6.5.1 --- k = 3 --- p.69 === Chapter 6.5.2 --- k = 4 --- p.70 === Chapter 6.5.3 --- Sum over all k --- p.71 === Chapter 6.6 --- "Strategy Ranking Theory Expressed in (Nkl-Nk,(l)" --- p.71 === Chapter 6.7 --- Summary --- p.73 === Chapter 7 --- Variance of the Attendance in MG: Data Collapse --- p.75 === Chapter 7.1 --- Previous Studies --- p.75 === Chapter 7.2 --- Attempt 1 --- p.76 === Chapter 7.2.1 --- Understanding from the Existing Theories --- p.76 === Chapter 7.2.2 --- Numerical Results --- p.79 === Chapter 7.3 --- Attempt 2 --- p.80 === Chapter 7.3.1 --- Modification Based on αc ß 1/2 --- p.81 === Chapter 7.3.2 --- Numerical Results --- p.81 === Chapter 7.4 --- Summary --- p.82 === Chapter 8 --- Minority Game in Networked Population --- p.83 === Chapter 8.1 --- Introduction --- p.83 === Chapter 8.2 --- Model --- p.84 === Chapter 8.3 --- Numerical Results --- p.85 === Chapter 8.4 --- Classification of Predictors --- p.86 === Chapter 8.4.1 --- Major Classification of Predictors - Hamming Distance D --- p.87 === Chapter 8.4.2 --- "Minor Classification of Predictors - Dynamical Ranking (k,1)" --- p.88 === Chapter 8.4.3 --- "Using the Classification (k,l, D)" --- p.89 === Chapter 8.5 --- "Winning Probability of a Predictor (wk,l,d)" --- p.89 === Chapter 8.5.1 --- "Odd Steps, k = 1" --- p.90 === Chapter 8.5.2 --- "Odd Steps, k = 2" --- p.91 === Chapter 8.6 --- Number of Predictors --- p.93 === Chapter 8.7 --- Mean Success Rate of Non-networked MG: m = 1 --- p.93 === Chapter 8.8 --- "Cluster Size of a Predictor (sk,l,D)" --- p.95 === Chapter 8.9 --- Mean Success Rate of Networked MG --- p.97 === Chapter 8.9.1 --- With wK(even)=0.5 --- p.97 === Chapter 8.9.2 --- "Modification of wK(even) Using skl,D" --- p.98 === Chapter 8.9.3 --- Modification of Using Modified wK(even) --- p.100 === Chapter 8.10 --- Variance of the Attendance in Networked MG --- p.101 === Chapter 8.11 --- Attendance Distribution --- p.103 === Chapter 8.12 --- A Network-type Independent Approach --- p.104 === Chapter 8.12.1 --- Degree Depending Success Rate --- p.104 === Chapter 8.12.2 --- Evaluating w(k) --- p.107 === Chapter 8.12.3 --- Application on Random Graph as Underlying Network --- p.108 === Chapter 8.13 --- The Position of the Minimum Variance --- p.108 === Chapter 8.14 --- Summary --- p.110 === Chapter 9 --- Conclusion --- p.111 === Bibliography --- p.115 |
author2 |
Chan, King Pak Keven. |
author_facet |
Chan, King Pak Keven. |
title |
Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
title_short |
Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
title_full |
Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
title_fullStr |
Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
title_full_unstemmed |
Strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
title_sort |
strategy dynamics, decision making, and global performance in agent-based models of competing populations. |
publishDate |
2006 |
url |
http://library.cuhk.edu.hk/record=b5896477 http://repository.lib.cuhk.edu.hk/en/item/cuhk-325528 |
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1719001173839577088 |
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ndltd-cuhk.edu.hk-oai-cuhk-dr-cuhk_3255282019-03-12T03:34:36Z Strategy dynamics, decision making, and global performance in agent-based models of competing populations. 競爭性系統個體模型中的策略動態、決策及整體表現 Strategy dynamics, decision making, and global performance in agent-based models of competing populations. Jing zheng xing xi tong ge ti mo xing zhong de ce lüe dong tai, jue ce ji zheng ti biao xian Statistical physics Game theory Chan King Pak Keven = 競爭性系統個體模型中的策略動態、決策及整體表現 / 陳景柏. Thesis submitted in: August 2005. Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. Includes bibliographical references (leaves vii-viii (4th gp.)). Text in English; abstracts in English and Chinese. Chan King Pak Keven = Jing zheng xing xi tong ge ti mo xing zhong de ce lüe dong tai, jue ce ji zheng ti biao xian / Chen Jingbo. Chapter 1 --- Introduction --- p.1 Chapter 2 --- Review on the Minority Game --- p.5 Chapter 2.1 --- Background --- p.5 Chapter 2.2 --- Model of MG --- p.6 Chapter 2.3 --- Features --- p.7 Chapter 2.3.1 --- Phase Transition --- p.7 Chapter 2.3.2 --- Inefficient and Efficient Phase --- p.8 Chapter 2.3.3 --- Anti-persistence --- p.9 Chapter 2.3.4 --- Data Collapse --- p.10 Chapter 2.4 --- Existing Theories --- p.10 Chapter 2.4.1 --- Reduced Strategy Space --- p.11 Chapter 2.4.2 --- The Crowd-Anticrowd Theory --- p.12 Chapter 2.5 --- Summary --- p.13 Chapter 3 --- Introduction to Strategy Ranking Theory --- p.15 Chapter 3.1 --- Strategy Ranking Theory for Mean Success Rate --- p.15 Chapter 3.1.1 --- Time evolution of Virtual Point Ranking --- p.15 Chapter 3.1.2 --- Winning Probability for m = 1 --- p.17 Chapter 3.2 --- Calculation of Mean Success Rate --- p.21 Chapter 3.3 --- "Size Dependence of weυen(K) (""Market Impact"" Effect)" --- p.23 Chapter 3.4 --- Size Dependence of wodd、K) (Uneven Distribution of Agents into Split Ranks) --- p.25 Chapter 4 --- Implementation of Strategy Ranking Theory --- p.30 Chapter 4.1 --- Feature of wodd(k) for higher m --- p.30 Chapter 4.2 --- Derivation of wodd(k) from Strategy Ranking Theory --- p.32 Chapter 4.3 --- Proof of Eq. (4.14) --- p.36 Chapter 4.4 --- Discussion on wodd(k) --- p.41 Chapter 4.4.1 --- Asymptotic Behavior of wodd(k) --- p.42 Chapter 4.4.2 --- Finite size correction of wodd(k) --- p.43 Chapter 5 --- Applications of Strategy Ranking Theory --- p.46 Chapter 5.1 --- Probability Density Function of Agents Making a Particular Choice --- p.46 Chapter 5.1.1 --- Odd time steps: k = 1 --- p.47 Chapter 5.1.2 --- Odd time steps: k = 2 --- p.48 Chapter 5.1.3 --- "Rodd,K" --- p.49 Chapter 5.1.4 --- Even time steps --- p.51 Chapter 5.1.5 --- Overall Attendance Distribution --- p.51 Chapter 5.2 --- The Variance of the Attendance --- p.52 Chapter 5.2.1 --- Asymptotic behavior of the variance --- p.54 Chapter 5.3 --- Anti-persistent Nature of Efficient Phase of MG --- p.55 Chapter 5.4 --- Summary --- p.58 Chapter 6 --- Strategy Ranking Theory and Crowd-Anticrowd Theory --- p.59 Chapter 6.1 --- Introduction --- p.59 Chapter 6.1.1 --- Strategy Ranking Theory --- p.60 Chapter 6.1.2 --- Crowd-Anticrowd Theory --- p.61 Chapter 6.2 --- Crowd-Anticrowd Theory with Ranking Patterns Characterized by k --- p.63 Chapter 6.3 --- Variance: Crowd-Anticrowd Theory --- p.65 Chapter 6.3.1 --- m = 1 --- p.65 Chapter 6.3.2 --- m = 2 --- p.66 Chapter 6.4 --- Variance: Modified Crowd-Anticrowd Theory for m̐ơح 1 --- p.66 Chapter 6.4.1 --- k = 0 --- p.67 Chapter 6.4.2 --- k = 1 --- p.67 Chapter 6.4.3 --- k = 2 --- p.67 Chapter 6.4.4 --- Sum over all k --- p.68 Chapter 6.5 --- Variance: Modified Crowd-Ant icrowd Theory for m=2 --- p.68 Chapter 6.5.1 --- k = 3 --- p.69 Chapter 6.5.2 --- k = 4 --- p.70 Chapter 6.5.3 --- Sum over all k --- p.71 Chapter 6.6 --- "Strategy Ranking Theory Expressed in (Nkl-Nk,(l)" --- p.71 Chapter 6.7 --- Summary --- p.73 Chapter 7 --- Variance of the Attendance in MG: Data Collapse --- p.75 Chapter 7.1 --- Previous Studies --- p.75 Chapter 7.2 --- Attempt 1 --- p.76 Chapter 7.2.1 --- Understanding from the Existing Theories --- p.76 Chapter 7.2.2 --- Numerical Results --- p.79 Chapter 7.3 --- Attempt 2 --- p.80 Chapter 7.3.1 --- Modification Based on αc ß 1/2 --- p.81 Chapter 7.3.2 --- Numerical Results --- p.81 Chapter 7.4 --- Summary --- p.82 Chapter 8 --- Minority Game in Networked Population --- p.83 Chapter 8.1 --- Introduction --- p.83 Chapter 8.2 --- Model --- p.84 Chapter 8.3 --- Numerical Results --- p.85 Chapter 8.4 --- Classification of Predictors --- p.86 Chapter 8.4.1 --- Major Classification of Predictors - Hamming Distance D --- p.87 Chapter 8.4.2 --- "Minor Classification of Predictors - Dynamical Ranking (k,1)" --- p.88 Chapter 8.4.3 --- "Using the Classification (k,l, D)" --- p.89 Chapter 8.5 --- "Winning Probability of a Predictor (wk,l,d)" --- p.89 Chapter 8.5.1 --- "Odd Steps, k = 1" --- p.90 Chapter 8.5.2 --- "Odd Steps, k = 2" --- p.91 Chapter 8.6 --- Number of Predictors --- p.93 Chapter 8.7 --- Mean Success Rate of Non-networked MG: m = 1 --- p.93 Chapter 8.8 --- "Cluster Size of a Predictor (sk,l,D)" --- p.95 Chapter 8.9 --- Mean Success Rate of Networked MG --- p.97 Chapter 8.9.1 --- With wK(even)=0.5 --- p.97 Chapter 8.9.2 --- "Modification of wK(even) Using skl,D" --- p.98 Chapter 8.9.3 --- Modification of Using Modified wK(even) --- p.100 Chapter 8.10 --- Variance of the Attendance in Networked MG --- p.101 Chapter 8.11 --- Attendance Distribution --- p.103 Chapter 8.12 --- A Network-type Independent Approach --- p.104 Chapter 8.12.1 --- Degree Depending Success Rate --- p.104 Chapter 8.12.2 --- Evaluating w(k) --- p.107 Chapter 8.12.3 --- Application on Random Graph as Underlying Network --- p.108 Chapter 8.13 --- The Position of the Minimum Variance --- p.108 Chapter 8.14 --- Summary --- p.110 Chapter 9 --- Conclusion --- p.111 Bibliography --- p.115 Chan, King Pak Keven. Chinese University of Hong Kong Graduate School. Division of Physics. 2006 Text bibliography print xviii, 117, [1], xii leaves : ill. ; 30 cm. cuhk:325528 http://library.cuhk.edu.hk/record=b5896477 eng chi Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) http://repository.lib.cuhk.edu.hk/en/islandora/object/cuhk%3A325528/datastream/TN/view/Strategy%20dynamics%2C%20decision%20making%2C%20and%20global%20performance%20in%20agent-based%20models%20of%20competing%20populations.jpghttp://repository.lib.cuhk.edu.hk/en/item/cuhk-325528 |