The Experts below are selected from a list of 92040 Experts worldwide ranked by ideXlab platform
Shaolin Tan - One of the best experts on this subject based on the ideXlab platform.
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characterizing the effect of population heterogeneity on Evolutionary Dynamics on complex networks
Scientific Reports, 2015Co-Authors: Shaolin TanAbstract:Recently, the impact of network structure on Evolutionary Dynamics has been at the center of attention when studying the Evolutionary process of structured populations. This paper aims at finding out the key structural feature of network to capture its impact on Evolutionary Dynamics. To this end, a novel concept called heat heterogeneity is introduced to characterize the structural heterogeneity of network, and the correlation between heat heterogeneity of structure and outcome of Evolutionary Dynamics is further investigated on various networks. It is found that the heat heterogeneity mainly determines the impact of network structure on Evolutionary Dynamics on complex networks. In detail, the heat heterogeneity readjusts the selection effect on Evolutionary Dynamics. Networks with high heat heterogeneity amplify the selection effect on the birth-death process and suppress the selection effect on the death-birth process. Based on the above results, an effective algorithm is proposed to generate selection adjusters with desired size and average degree.
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When Structure Meets Function in Evolutionary Dynamics on Complex Networks
IEEE Circuits and Systems Magazine, 2014Co-Authors: Shaolin Tan, Guanrong Chen, David J. HillAbstract:Evolutionary Dynamics play a fundamental role in exploring the underlying mechanism of collective behaviors over a multi-agent network. Traditionally, Evolutionary Dynamics focus on the analysis of Evolutionary behaviors of unstructured complex systems. However, recent research reveals that system structure is essential in the formation of collective behaviors. This article shows the intrinsic relation between structure and function of a complex dynamical network with Evolutionary Dynamics. In particular, the impact of node Dynamics and network structure on Evolutionary Dynamics is investigated. Methods are given to find invasion hubs of a network and to design efficient networks for innovation diffusion. Moreover, it discusses some potential real-world applications and highlights some challenging problems for future studies.
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Characterizing the effect of network structure on Evolutionary Dynamics via a novel measure of structural heterogeneity
2013 25th Chinese Control and Decision Conference (CCDC), 2013Co-Authors: Shaolin Tan, David J. HillAbstract:Recently, the study of Evolutionary Dynamics on structured population has attracted an increasing attention in various fields. This paper aims at investigating the effect of network structure on Evolutionary Dynamics. In detail, a novel measure of structural heterogeneity is introduced to characterize the network structure effect on Evolutionary Dynamics. By simulating the Evolutionary Dynamics of invasion process on a massive amount of randomly sampled networks, we find that structural heterogeneity amplifies the selective effect on fixation probability of invader in birth-death process, however, it weakens the selective effect in death-birth process. These findings provide a fundamental principle for designing selection amplifier, which benefits advantageous invaders while inhibits unadvantageous ones. Moreover, an effective algorithm is proposed to generate selection amplifiers with specified size and average degree.
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ISCAS - Exploring Evolutionary Dynamics in a class of structured populations
2012 IEEE International Symposium on Circuits and Systems, 2012Co-Authors: Shaolin Tan, David J. HillAbstract:It is well known that the selection of fixation probability is the fundamental problem for the Evolutionary Dynamics in structured populations. This paper aims to introduce a general approach for investigating the Evolutionary Dynamics in a class of structured populations. It includes the Evolutionary game Dynamics and constant selection Dynamics with different asynchronous updating rules, such as ‘birth-death’, ‘voter model’, ‘death-birth’, and ‘imitation’. It should be pointed out that the proposed method provides an effective way to resolve the Evolutionary Dynamics on general graphs. In particular, it introduces a useful calculating tool to analyze various Evolutionary Dynamics on small order graphs.
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IECON - Monotonicity of fixation probability of Evolutionary Dynamics on complex networks
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012Co-Authors: Shaolin Tan, David J. HillAbstract:It is well known that the Evolutionary Dynamics characterizes the process of competition and evolution of phenotypes and behaviors in a population. Intuitively, the individual with a higher fitness will have a higher survival probability, which should be reflected in the Evolutionary dynamic model. However, due to the computational complexity of fixation probability, it is very difficult to prove the existence of this property in Evolutionary Dynamics on complex networks. This paper aims at providing a rigorously theoretical proof for the global existence of such property in the local Evolutionary Dynamics by using the coupling and splicing techniques. In particular, we also prove that the fixation probability is monotone increasing for the initial nodes set of mutants. Numerical simulations are also given to validate the proposed approaches.
Jeff S. Shamma - One of the best experts on this subject based on the ideXlab platform.
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Passivity Analysis of Higher Order Evolutionary Dynamics and Population Games
arXiv: Optimization and Control, 2016Co-Authors: Mohamed A. Mabrok, Jeff S. ShammaAbstract:In population games, a large population of players, modeled as a continuum, is divided into subpopulations, and the fitness or payoff of each subpopulation depends on the overall population composition. Evolutionary Dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population games, namely so-called "stable games". In particular, it was shown that a combination of stable games and (an analogue of) passive Evolutionary Dynamics results in stable convergence to Nash equilibrium. This paper considers the converse question of necessary conditions for Evolutionary Dynamics to exhibit stable behaviors for all generalized stable games. Here, generalization refers to "higher order" games where the population payoffs may be a dynamic function of the population state. Using methods from robust control analysis, we show that if an Evolutionary dynamic does not satisfy a passivity property, then it is possible to construct a generalized stable game that results in instability. The results are illustrated on selected Evolutionary Dynamics with particular attention to replicator Dynamics, which are also shown to be lossless, a special class of passive systems.
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CDC - Passivity analysis of higher order Evolutionary Dynamics and population games
2016 IEEE 55th Conference on Decision and Control (CDC), 2016Co-Authors: Mohamed A. Mabrok, Jeff S. ShammaAbstract:Evolutionary Dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population games, namely so-called “stable games”. In particular, it was shown that a combination of stable games and (an analogue of) passive Evolutionary Dynamics results in stable convergence to Nash equilibrium. This paper considers the converse question of necessary conditions for Evolutionary Dynamics to exhibit stable behaviors for all generalized stable games. Using methods from robust control analysis, we show that if an Evolutionary dynamic does not satisfy a passivity property, then it is possible to construct a generalized stable game that results in instability. The results are illustrated on selected Evolutionary Dynamics with particular attention to replicator Dynamics, which are also shown to be lossless, a special class of passive systems.
David J. Hill - One of the best experts on this subject based on the ideXlab platform.
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When Structure Meets Function in Evolutionary Dynamics on Complex Networks
IEEE Circuits and Systems Magazine, 2014Co-Authors: Shaolin Tan, Guanrong Chen, David J. HillAbstract:Evolutionary Dynamics play a fundamental role in exploring the underlying mechanism of collective behaviors over a multi-agent network. Traditionally, Evolutionary Dynamics focus on the analysis of Evolutionary behaviors of unstructured complex systems. However, recent research reveals that system structure is essential in the formation of collective behaviors. This article shows the intrinsic relation between structure and function of a complex dynamical network with Evolutionary Dynamics. In particular, the impact of node Dynamics and network structure on Evolutionary Dynamics is investigated. Methods are given to find invasion hubs of a network and to design efficient networks for innovation diffusion. Moreover, it discusses some potential real-world applications and highlights some challenging problems for future studies.
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Characterizing the effect of network structure on Evolutionary Dynamics via a novel measure of structural heterogeneity
2013 25th Chinese Control and Decision Conference (CCDC), 2013Co-Authors: Shaolin Tan, David J. HillAbstract:Recently, the study of Evolutionary Dynamics on structured population has attracted an increasing attention in various fields. This paper aims at investigating the effect of network structure on Evolutionary Dynamics. In detail, a novel measure of structural heterogeneity is introduced to characterize the network structure effect on Evolutionary Dynamics. By simulating the Evolutionary Dynamics of invasion process on a massive amount of randomly sampled networks, we find that structural heterogeneity amplifies the selective effect on fixation probability of invader in birth-death process, however, it weakens the selective effect in death-birth process. These findings provide a fundamental principle for designing selection amplifier, which benefits advantageous invaders while inhibits unadvantageous ones. Moreover, an effective algorithm is proposed to generate selection amplifiers with specified size and average degree.
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ISCAS - Exploring Evolutionary Dynamics in a class of structured populations
2012 IEEE International Symposium on Circuits and Systems, 2012Co-Authors: Shaolin Tan, David J. HillAbstract:It is well known that the selection of fixation probability is the fundamental problem for the Evolutionary Dynamics in structured populations. This paper aims to introduce a general approach for investigating the Evolutionary Dynamics in a class of structured populations. It includes the Evolutionary game Dynamics and constant selection Dynamics with different asynchronous updating rules, such as ‘birth-death’, ‘voter model’, ‘death-birth’, and ‘imitation’. It should be pointed out that the proposed method provides an effective way to resolve the Evolutionary Dynamics on general graphs. In particular, it introduces a useful calculating tool to analyze various Evolutionary Dynamics on small order graphs.
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IECON - Monotonicity of fixation probability of Evolutionary Dynamics on complex networks
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012Co-Authors: Shaolin Tan, David J. HillAbstract:It is well known that the Evolutionary Dynamics characterizes the process of competition and evolution of phenotypes and behaviors in a population. Intuitively, the individual with a higher fitness will have a higher survival probability, which should be reflected in the Evolutionary dynamic model. However, due to the computational complexity of fixation probability, it is very difficult to prove the existence of this property in Evolutionary Dynamics on complex networks. This paper aims at providing a rigorously theoretical proof for the global existence of such property in the local Evolutionary Dynamics by using the coupling and splicing techniques. In particular, we also prove that the fixation probability is monotone increasing for the initial nodes set of mutants. Numerical simulations are also given to validate the proposed approaches.
Giovanni Ponti - One of the best experts on this subject based on the ideXlab platform.
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Continuous-time Evolutionary Dynamics: Theory and Practice
Social Science Research Network, 2000Co-Authors: Giovanni PontiAbstract:This paper surveys some recent developments in the literature which studies continuous-time Evolutionary Dynamics in the context of economic modelling. Copyright 2000 University of Venice
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Continuous-time Evolutionary Dynamics: theory and practice
Research in Economics, 2000Co-Authors: Giovanni PontiAbstract:This paper surveys some recent developments in the literature which studies continuous-time Evolutionary Dynamics in the context of economic modeling.
Mohamed A. Mabrok - One of the best experts on this subject based on the ideXlab platform.
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Passivity Analysis of Higher Order Evolutionary Dynamics and Population Games
arXiv: Optimization and Control, 2016Co-Authors: Mohamed A. Mabrok, Jeff S. ShammaAbstract:In population games, a large population of players, modeled as a continuum, is divided into subpopulations, and the fitness or payoff of each subpopulation depends on the overall population composition. Evolutionary Dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population games, namely so-called "stable games". In particular, it was shown that a combination of stable games and (an analogue of) passive Evolutionary Dynamics results in stable convergence to Nash equilibrium. This paper considers the converse question of necessary conditions for Evolutionary Dynamics to exhibit stable behaviors for all generalized stable games. Here, generalization refers to "higher order" games where the population payoffs may be a dynamic function of the population state. Using methods from robust control analysis, we show that if an Evolutionary dynamic does not satisfy a passivity property, then it is possible to construct a generalized stable game that results in instability. The results are illustrated on selected Evolutionary Dynamics with particular attention to replicator Dynamics, which are also shown to be lossless, a special class of passive systems.
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CDC - Passivity analysis of higher order Evolutionary Dynamics and population games
2016 IEEE 55th Conference on Decision and Control (CDC), 2016Co-Authors: Mohamed A. Mabrok, Jeff S. ShammaAbstract:Evolutionary Dynamics describe how the population composition changes in response to the fitness levels, resulting in a closed-loop feedback system. Recent work established a connection between passivity theory and certain classes of population games, namely so-called “stable games”. In particular, it was shown that a combination of stable games and (an analogue of) passive Evolutionary Dynamics results in stable convergence to Nash equilibrium. This paper considers the converse question of necessary conditions for Evolutionary Dynamics to exhibit stable behaviors for all generalized stable games. Using methods from robust control analysis, we show that if an Evolutionary dynamic does not satisfy a passivity property, then it is possible to construct a generalized stable game that results in instability. The results are illustrated on selected Evolutionary Dynamics with particular attention to replicator Dynamics, which are also shown to be lossless, a special class of passive systems.
