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相关论文: Unified "micro"- and "macro-" evolution of eco-sys…

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We develop a ``unified'' model that describes both ``micro'' and ``macro'' evolutions within a single theoretical framework. The eco-system is described as a dynamic network; the population dynamics at each node of this network describes…

统计力学 · 物理学 2013-05-29 Debashish Chowdhury , Dietrich Stauffer , Ambarish Kunwar

Ecology and evolution are inseparable. Motivated by some recent experiments, we have developed models of evolutionary ecology from the perspective of dynamic networks. In these models, in addition to the intra-node dynamics, which…

种群与进化 · 定量生物学 2009-11-10 Debashish Chowdhury , Dietrich Stauffer

We incorporate the generic hierarchical architecture of foodwebs into a "{\it unified}" model that describes both "micro" and "macro" evolutions within a single theoretical framework. This model describes the "micro" -evolution in detail by…

统计力学 · 物理学 2009-11-10 Debashish Chowdhury , Dietrich Stauffer

We have generalized our ``unified'' model of evolutionary ecology by taking into account the possible movements of the organisms from one ``patch'' to another within the same eco-system. We model the spatial extension of the eco-system…

种群与进化 · 定量生物学 2009-11-10 Dietrich Stauffer , Ambarish Kunwar , Debashish Chowdhury

Recently we have extended our the "unified" model of evolutionary ecology to incorporate the {\it spatial inhomogeneities} of the eco-system and the {\it migration} of individual organisms from one patch to another within the same…

种群与进化 · 定量生物学 2009-11-10 Ambarish Kunwar

Motivated by the results of recent laboratory experiments (Yoshida et al. Nature, 424, 303-306 (2003)) as well as many earlier field observations that evolutionary changes can take place in ecosystems over relatively short ecological time…

种群与进化 · 定量生物学 2007-05-23 Debashish Chowdhury , Dietrich Stauffer

We propose a general scenario to analyze social and economic changes in modern environments. We illustrate the ideas with a model that incorporating the main trends is simple enough to extract analytical results and, at the same time,…

统计力学 · 物理学 2009-10-31 A. Arenas , A. Diaz-Guilera , C. J. Perez , F. Vega-Redondo

We view Digital Ecosystems to be the digital counterparts of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can automatically solve complex, dynamic problems. So, this work is…

多智能体系统 · 计算机科学 2009-10-06 Gerard Briscoe

Evolution gave rise to creatures that are arguably more sophisticated than the greatest human-designed systems. This feat has inspired computer scientists since the advent of computing and led to optimization tools that can evolve complex…

神经与进化计算 · 计算机科学 2020-12-23 Jean-Baptiste Mouret

The mutual influence of dynamics and structure is a central issue in complex systems. In this paper we study by simulation slow evolution of network under the feedback of a local-majority-rule opinion process. If performance-enhancing local…

物理与社会 · 物理学 2009-11-13 Zhen Shao , Haijun Zhou

We propose a generic model of eco-systems, with a {\it hierarchical} food web structure. In our computer simulations we let the eco-system evolve continuously for so long that that we can monitor extinctions as well as speciations over…

种群与进化 · 定量生物学 2009-11-10 Debashish Chowdhury , Dietrich Stauffer

We introduce a simple computational model that, with a microscopic dynamics driven by natural selection and mutation alone, allows the description of true speciation events. A statistical analysis of the so generated evolutionary tree…

种群与进化 · 定量生物学 2009-11-11 V. Schwammle , E. Brigatti

We consider networks of dynamical units that evolve in time according to different laws, and are coupled to each other in highly irregular ways. Studying how to steer the dynamics of such systems towards a desired evolution is of great…

物理与社会 · 物理学 2020-12-01 Ricardo Gutiérrez , Massimo Materassi , Stefano Focardi , Stefano Boccaletti

The evolution of the Internet has manifested itself in many ways: the traffic characteristics, the interconnection topologies and the business relationships among the autonomous components. It is important to understand why (and how) this…

网络与互联网体系结构 · 计算机科学 2012-11-27 Richard T. B. Ma , John C. S. Lui , Vishal Misra

We view Digital Ecosystems to be the digital counterparts of biological ecosystems, exploiting the self-organising properties of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can…

神经与进化计算 · 计算机科学 2009-10-05 G. Briscoe , P. De Wilde

We investigate the self-organising behaviour of Digital Ecosystems, because a primary motivation for our research is to exploit the self-organising properties of biological ecosystems. We extended a definition for the complexity, grounded…

神经与进化计算 · 计算机科学 2012-01-25 Gerard Briscoe , Philippe De Wilde

We create a novel optimisation technique inspired by natural ecosystems, where the optimisation works at two levels: a first optimisation, migration of genes which are distributed in a peer-to-peer network, operating continuously in time;…

神经与进化计算 · 计算机科学 2012-11-26 Gerard Briscoe , Philippe De Wilde

The interaction between natural selection and random mutation is frequently debated in recent years. Does similar dilemma also exist in the evolution of real networks such as biological networks? In this paper, we try to discuss this issue…

统计力学 · 物理学 2009-01-07 Zhen Shao , Hai-jun Zhou

We consider the effect of network structure on the evolution of a population. Models of this kind typically consider a population of fixed size and distribution. Here we consider eco-evolutionary dynamics where population size and…

种群与进化 · 定量生物学 2023-04-05 Karan Pattni , Wajid Ali , Mark Broom , Kieran J Sharkey

An important feature of many complex systems, both natural and artificial, is the structure and organization of their interaction networks with interesting properties. Here we present a theory of self-organization by evolutionary adaptation…

适应与自组织系统 · 物理学 2007-05-23 Venkat Venkatasubramanian , Santhoji Katare , Priyan R. Patkar , Fangping Mu
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