Group photo-1 Group photo-2 Hans Herrmann (ETHZ, Swiss Federal Institute of Technology Zurich) Prof. Yi-Cheng Zhang and Jianwei Zhang Prof. Zhang Jianwei talk Self introduction by Li Xin-Ye Self introduction by Liu Yi-min Self introduction by Yang Hui-Jie Sept 16 Afternoon Meeting a Sept 16 Afternoon Meeting b Lunch Sept 16 a Lunch Sept 16 b
Collective Picture 1 集体照-2 Professor Fred von Gunten （ ISC, Uni Fribourg ）Talk: Complexity of systems with respect to the economy and society CCNU 辜姣 Dinner Sept.17 a Dinner Sept.17 b Dinner Sept.17 c Dinner Sept.17 d
2011 EU-China Workshop on Complexity Science Talk Abstract TAIPEX —An Online ExperimentalPlatform to Study Market Behavior Sai-Ping Li Institute of Physics, Academia Sinica, Taipei 115, Taiwan The TAIPEX , which is one of the existing prediction market platforms in the world, was first set up in early 2004 in Taiwan as an experimental toolto study the voting behavior of the people in Taiwan. After the first successful experimental launchon this platform, it was soon realized that one couldin fact study financial market behaviors by using this platform. In subsequent years, that is, from early 2004 till theend of 2010, eight experiments have been carried out onthis prediction market platform. These include: three presidential elections (2 from Taiwan and one from the US), one parliamentary election, three city mayor elections and one on bird flu. From the results of these experiments, we have observed many stylized facts that are known to exist in everyday financial markets. For example, Figure 1 shows the probability density of normalized price returns of TAIPEX in the 2004 Taiwan parliamentary election with different time lagsequal to 55(red), 148(black), 403(yellow), 1097(green) and 8103(blue) minutes. The figure illustrates two interesting features. The firstfeature is the heavy tails onthe two ends ofthe curves. One can see this easily when compared to a Gaussian distribution as shown in the figure. Heavy tails of price returns in financial markets arestylized facts that are knownto market practitionersfor a long timeand our experiments also exhibitsuch a feature. Another feature that we can observe in this figure is the universality of different time lag curves. One can see that the different time lag curves can indeed be represented by a single distribution curve. We also observe that other well known stylized facts also appear in our prediction mark Figure 1. Probability density of normalized price returns with time lag equal to 55(red), 148(black), 403(yellow), 1097(green) and 8103(blue) minutes. The dashed line was obtained from a Cauchy distribution and the dotted line is a Gaussian distribution of unit variance. Aside from the already well known stylized facts, we have further uncovered many features that are likely to exist but are unable to be detected in financial markets. Take, for example, we can construct a trading network of the traders from the data of the experiment on this prediction market platform . The same kind of networkis unlikely to be constructed due to the lack of data availabilityin real financial markets. Figure 2 is an illustration of a trading network among traders of our experiment on the 2006 Taipei Mayor Election. The network is based on the data from Day 3. The number of traders and the trading network grew sincetherewere more registered players to do trading on the platformas the experiment continueduntil the dayof the election. Figure 2. The trading network on Day 3 of the 2006 Taipei Mayor Election experiment. The network consists of 40 interconnected nodes. isolated nodes are not shown here . In this talk, we will first give abrief introduction of the historical development and the current status ofprediction markets. As an example of how prediction markets work, we will give details of doingtrading on our prediction market platform. Results of our previous experiments will be summarized and presented, including the most recent experiment done by the end of 2010. Possible future work will beproposed and discussed. Most importantly, collaborations on this prediction market platform are welcome. References: http://socioecono.phys.sinica.edu.tw/ K.J. Arrow et.al., Science 320(2008)877-8 G. Tziralis and I. Tatsiopoulos, “Prediction Markets: An Extended Literature Review”, TheJournal of Prediction Markets 1(2007)75-91. S.C. Wang et.al., “Statistical Properties of an Experimental Political Futures Market”, Quantitative Finance 9(2009)9-16. S.C. Wang et.al., “Network Topology of an Experimental Futures Exchange”, European Physical Journal B62(2008)105-111. Piecewise Smooth Lyapunov Function for a Nonlinear Dynamical System Yan Gao Business School, University of Shanghai for Science and Technology, Shanghai 200093, China email:gaoyan@usst.edu.cn In this paper, stability and attraction for a nonlinear dynamical system with nonsmooth Lyapunov function are studied. The previous results on stability and attraction with a max-type Lyapunov function are extended to the case where Lyapunov function is piecewise smooth. A condition, under which stability and attraction is guaranteed with a piecewise smooth Lyapunov function, is proposed. Taking two certain classes of piecewise smooth functions as Lyapunov functions, related conditions for stability and attraction are developed. Key Words. Nonlinear dynamical system, stability, region of attraction, Lyapnov functions, nonsmooth analysis, piecewise smooth function. Hurst Exponents for Short Time Series 短时间序列的分形指数 Jingchao Qi, and Huijie Yang Biz School, University of Shanghai for Science and Technology, A new concept, called balanced estimator of diffusion entropy, is proposed to detect scaling in short time series. The effectiveness of the method is verified by means of a large number of artificial fractional Brownian motions. It is used also to detect scaling properties and structural breaks in stock price series of Shanghai Stock market. PACS ： 05.45.T, 89.75.D, 05.40.F, 05.40 Keyword(s); short time series; scaling; diffusion entropy Global Compact Representation of Continuous Piecewise Linear Functions and Its Application Xin-Ye Li Business School, University of Shanghai for Science and Technology, Shanghai 200093, China Critical point and critical cluster distribution of explosive site percolation in random network Yu-gang Ma 1) and Ding-ding Han 2) 1 Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China 2 School of Information Science and Technology, East China Normal University, Shanghai 2000241, China Recently a new kind of percolation, named explosive percolation was proposed. By introducing a proper competitive mechanism, it was first found by Achlioptas, D'Souza, and Spencer and was subsequently studied intensely by other scientists that the bond percolation in random networks became discontinuous. Such kind of percolation has a delayed transition point but still maintain a power-law critical cluster distribution with yet the exponent different from the classical one, indicating the absence of universality in sense of different percolation strategies. However further numerical and theoretical studies have provided evidences that the bond explosive percolation in random network is actually continuous in the thermodynamics limit except for the global competitive case in which all the links in network participate in the selection. Although the argument still exists, explosive percolation has brought new insights to the percolation theory. However the two most important properties, namely the location of the critical point and the critical cluster distribution have not been studied systematically. Previous studies presented the related results only for their special models, which neither provide any general conclusions nor help to understand the possible universal behavior. In this letter, we focus on this problem instead of just studying the continuity of explosive percolation. By introducing a best-of-m competitive rule the explosive site percolation in ER network is studied. We prove that the critical point tc(m, k) has a nontrivial limitation Tc(k) 1 as m = N →∞. By developing a finite size scaling method, Tc(k) is found to scale asymptotically as . The result is further generalized by for all m with approximated by an arctan function. The critical cluster distribution is found to be power law with exponent about -2.5 regardless of m, leading to a conjecture that the universality remains in sense of different percolation strategy. The continuity of the percolation is also discussed. The present results basically generalize the classical conclusion to adapt to a large class of explosive percolation. Key words: explosive percolation, random network, critical point, critical cluster distribution Fluctuation scaling in complex networks Ding-ding Han School of Information Science and Technology, East China Normal University, Shanghai 200241, China Fluctuation is a universal phenomenon in complex networks. Since L.R.Taylor’s influential paper on natural populations was published in 1961, a scaling relationship has been observed in a wide range of disciplines, ranging from population dynamics through the Internet to the stock market. The original law exhibits that for any fixed species there is a power-law scaling between fluctuations in the size of a population (characterized by standard deviation) and the average population, namely In this paper, brief introduction about fluctuation scaling is given. The fluctuation can be divided into temporal fluctuation scaling and ensemble fluctuation scaling. Besides, we have investigated the evolution of the download network for the rank-ordered papers which were listed in Zhang’s Econophysics web page. From 2004 to 2007, the download distribution shows the change of the exponents even though the rank-ordered distribution still keeps scale-free feature, reflecting the change of traffic on nodes which represent the given downloaded papers. Further, we give a quantitative analysis for the average download rates per day, which shows day-by-day fluctuation. The average flux shows a fast exponential decay as a function of the rank, while the dispersion does not show an obvious dependence of the rank. Interestingly, the dispersion of the download rate distributions shows power-law scaling behavior with its average flux, namely . In different time windows ranging from about 6.5 months to 31 months in which the download distributions are accumulated, the scaling parameter changes with the time windows, namely from 0.60 to 0.89. The origins are qualitatively interpreted by two models. Future work on quantitative model simulation and a possible -scaling of network fluctuation is in progress. Key words: Fluctuation scaling; complex netwrks; random walker model; fluctuation exponent; time window Long division unites - long union divides, A model for cultural evolution J. Jiang, R. Wang, Michel Pezeril, and Q.A. Wang One of the historical phenomena in the time evolution of cultural, national and economic systems is the transition between union and division of one or several entities. In this work, we propose a union-division model based on the maxim "long union divides and long division unites" in order to investigate the long time behaviors of the networks composed of nodes representing the above mentioned entities. Each node is characterized by several quantities such as identity, ingredient, richness, and age. The time evolution of the network is probabilistic depending on the above quantities and on the interaction between the neighboring n nodes. This work offers a long term view on the apparently periodic dynamics of an ensemble of cultural entities. Self-organization and Preconditions of Efficient Markets You-Gui Wang Department of Systems Science, School of Management, Beijing Normal University, Beijing 100875, China, Email: ygwang@bnu.edu.cn Most of economists have devoted themselves into proving the existence of “invisible hand” in marketing systems. Traditional approaches claim that an efficient market lies on three presuppositions: rationality of individual market participants, complete information and equilibrium of the market. These presumptions result from the static postulations of mainstream economics. In this talk, I will show that from dynamic perspective a market can achieve an efficient state without those strong assumptions. The patterns of self-organization of an evolutionary market are displayed where the premises of individual rationality, single price as well as equilibrium are abandoned. Keywords: Market efficiency, Self-organization, Rationality, Market equilibrium, Dynamic structure. Accelerating growth and size-dependent distribution of human online activities Zhang Jiang Department of Systems Science, School of Management, Beijing Normal University, Beijing 100875, China, Research on human online activities usually assumes that total activity T increases linearly with active population P, that is, T ∝ P^γ (γ = 1). However, we find examples of systems where total activity grows faster than active population. Our study shows that the power law relationship T ∝ P^γ (γ 1) is in fact ubiquitous in online activities such as microblogging, news voting, and photo tagging. We call the pattern “accelerating growth” and find it relates to a type of distribution that changes with system size. We show both analytically and empirically how the growth rate γ associates with a scaling parameter b in the size-dependent distribution. As most previous studies explain accelerating growth by power law distribution, the model of size-dependent distribution is worth further exploration. Statistics and Evolution of Donations for 2008 Wenchuan Earthquake Qinghua Chen ( 陈清华 ), Yajing Wu ( 吴亚晶 ), Jinzhong Guo( 郭金忠 ), Yougui Wang( 王有贵 ) Department of Systems Science, School of Management, Beijing Normal University, Beijing 100875, People's Republic of China qinghuachen@bnu.edu.cn (86-10-58802732) Based on the data of individual donations from Chinese Red Cross Foundation , this paper analyzes and discusses the distribution of individual donations and evolutions of some statistical properties over time. The results show: 1) individual donations distribution has shown some power law characters, and some donation numbers are preferred; 2) the growths of person times and total donations obey Logistic growth, and the growth of person times is ahead of another; 3) the trend of average donations amount is that, firstly decreases and then increase, with large donations coming at a subsequent time or stage . This paper proposes a multi-agent model to simulate donations’ evolution based information diffusion. Figure 1. Zipf’s plot of donations Figure 2. Pareto’s plot of donation Figure 3. The growths of donations amount and person times, and the fitting of Logistic curve Figure 4. The daily average of the accumulated donations amount Keywords : individual donations, power law, logistic growth Perspectives of several directions in recent complex system research Bing-Hong Wang Department of Modern Physics, University of Science and Technology of China Hefei, 230026, China and The Research Center for Complex Systems, University of Shanghai for Science and Technology, Shanghai, 200093, China bhwang@ustc.edu.cn Study of the evolutionary games on complex networks We study the evolutionary games on complex networks, including the prisoner's dilemma game and the public goods game. Our research focus is how the clustering structure, social diversity and aspiration-induced migration affect the cooperative behavior. We find that the higher clustering coefficient enhances the cooperation in spatial public goods game. Due to the existence of social diversity, the influence of different individuals is different. The influence of an individual is defined as the power of its degree, where the power exponent is an adjustable parameter. During the evolutionary process, every individual chooses one of its neighbors as a reference with a probability proportional to the influence of the neighbor. It is found that for the fixed value of the temptation to defect, there exists an optimal value of , leading to the highest level of cooperation. We propose an aspiration-induced migration in which individuals will migrate to new sites provided that their payoffs are below some aspiration level. It is found that moderate aspiration level can best favor cooperative behavior. Cooperation percolation in spatial evolutionary games is specially considered. We study the dynamical organization of cooperator clusters in prisoner’s dilemma game on regular and complex networks. It has been found that when the initial concentration of cooperators in the systems exceeds a threshold, there is a phase transition characterized by the emergence of a giant spanning cooperative cluster of the order of network size. Depending on the network structure and the temptation to defect, the phase transition appears to belong to different universality classes of percolation, including regular percolation, invasion percolation and other unreported classes. Transportation Dynamics on Mobile Node Network Most existing works on transportation dynamics focus on the networks of a fixed structure, but networks whose nodes are mobile have become widespread, such as cell-phone networks. We introduce a model to explore the basic physics of transportation on mobile networks. Of particular interest are the dependence of the throughput on speed of agent movement and communication range. Our computations reveal a hierarchical dependence for the former, while for the latter we find an algebraic power law between the throughput and the communication range with an exponent determined by the speed. We develop a physical theory based on the Fokker-Planck equation to explain these phenomena. Our findings provide insights into complex transportation dynamics arising commonly in natural and engineering systems. Reference: Phys.Rev.E 83.016102(2011) Newsbag, an adaptive model for news recommendation Dott. Giulio Cimini Uni Fribourg and Univ. Rome, Italy We propose an adaptive recommendation model which combines similarities in users' rating patterns with epidemic-like spreading of news on an evolving social network. Our system has high filtering efficiency and robustness against malicious behavior, and outperforms other widely adopted recommendation methods. The model also sheds light on who people do follow in social communities and where they do search for good information sources. Agenetic perspective on citation networks Dott. Stanislao Gualdi Uni Fribourg and Univ. Rome, Italy we develop an analytical framework to asses genetic relations between papers. We show that such framework can be used both to highlight papers which play a fundamental role in the development of a research field both to build a recommender system which filters relevant literature for a given interest. The spectral analysis for biology networks Jiao Gu （ 辜姣） Central China Normal University ， Wuhan ， P.R.China We constructed the protein network and domain networks from the database. Baced on the analysis ofspectrumof normalized Laplacian matrix, we could classify the networks and find phylogenetic information from these networks. Statistical Mechanics of Social Tagging Networks: Structure, Dynamics and Function Zike Zhang （张子柯） University of Fribourg, Switzerland In this talk, I would introduce our recent progress on the study of social tagging netowks, including the structure of how to describe and measure it, the dynamics of how it evolves and it application in recommender systems. It is expected to give a general picture of Social Tagging Networks and possible research topics, as well as challenges. Potentials of sino-european cooperations in complexity sciences Jian-Wei Zhang University of Hamburg ， Hamburg ， German European and China cooperation opportunities in Complexity Sciences Jeff Johnson Open University, London, UK Complexity of systems with respect to the economy and society Dr. Fred von Gunten International Strategy and Competition University of Fribourg ， Switzerland “Complexity research as an interdisciplinary undertaking is concerned with the question how orders, structures, chaos and break downs can be created by the relationships of many elements of a complex system… The object of complexity research is to identify and understand chaos, tensions and conflicts in complex systems (molecules in materials, cellules in organisms or human beings in markets and organisations) so as to acquire new knowledge for the potential of establishing new orders.” Mainzer, 2008, Komplexitt, p. 10). When this definition is applied to the economy and society then a number of difficulties have to be overcome. In this contribution one attempts to explain how three basic propositions contribute to improving the situation. First, market or state capitalism must be identified as organised socio-economic systems. Second, these systems must be presented as three level economies instead of only two level economies. Third, in the end, “pure analysis” in the economic and social sciences must be integrated with the other sub-systems of the nation-state, at the international level with international organisations. That way the degree of complexity of systems with respect to the economy and society can be positively influenced
2011 EU-China Workshop on Complexity Science Venue ： University of Fribourg ， Switzerland Time ： Sept 14-19, 2011 Scientific Program Scientific Board Yi-Cheng Zhang (Chair) University of Fribourg, Switzerland Bing-Hong Wang (Chair) University of Science and Technology of China, Hefei, P.R. China Jeff Johnson Open University, London, UK Jian-Wei Zhang University of Hamburg, German Yan Gao University of Shanghai for Science and Technology ， China Sai-Ping Li Institute of Physics, Academia Sinica, Taiwan Xu Cai Central China Normal University,Wuhan ， P.R. China You-Gui Wang Beijing Normal University, Beijing, P.R. China Local Organizing Committee at University of Fribourg Miss. Pei Wu （吴培） , Mr. Ting Lei （雷庭） , Mr. Hao Liu （刘浩） , Mr. Yun Ye （叶云） , Mr. Cheng-jun Zhang （张成军） Dr. Matus Medo , Dr. Giulio Cimini, Dr. Stanislao GUALDI Invited Speakers Yan Gao （高岩） University of Shanghai for Science and Technology, Shanghai, China Guang-Le Yan （严广乐） University of Shanghai for Science and Technology, Shanghai, China Xing-Ye Li （李星野） University of Shanghai for Science and Technology, Shanghai, China Hui-Jie Yang （杨会杰） University of Shanghai for Science and Technology, Shanghai, China Sai-Ping Li （李世炳） Institute of Physics, Academia Sinica ， Taiwan Bing-Hong Wang （汪秉宏） University of Science and Technology of China You-Gui Wang （王有贵） Beijing Normal University P.R.China Jiang Zhang （张江） Beijing Normal University P.R.China Qing-Hua Chen （陈清华） Beijing Normal University P.R.China Ding-Ding Han （韩定定） East China Normal University P.R.China Yu-Gang Ma （马余刚） Shanghai Institute of Applied Physics, Chinese Academy of Sciences ， Shanghai ， P.R.China Xu Cai （蔡勖） Central China Normal University ， Wuhan ， P.R.China Jian Jiang（江健） Central China Normal University ， Wuhan ， P.R.China Jiao Gu （ 辜姣） Central China Normal University ， Wuhan ， P.R.China Yi-Min Liu （刘益民） Shaoguan University, Guangdong, P.R.China Zike Zhang （张子柯） University of Fribourg, Switzerland Jian-Wei Zhang ， University of Hamburg ， Hamburg ， German Jeff Johnson ， Open University, London, UK Fred von Gunten, International Strategy and Competition, University of Fribourg ， Switzerland Luciano Pietronero ， University of Rome ， Italy Paul Ormerod ， Volterra consulting, Lond ， United Kingdom Bridget Rosewell ， Volterra consulting Andrzej Nowak ， University of Warsaw ， Poland David Hall ， Open University, London, UK Hans Herrmann ， Swiss Federal Institute of Technology Zurich ， Switzerland Danial Stauffacher ， ICT4Peace, Geneva ， Switzerland PROGRAM Wednsday, Sept 14: Arriving at Zurich Thursday, Sept 15: Traveling to Bern（伯尔尼）, Lu Saien （ 卢塞恩） ， INTERLAKEN （因特拉肯，少女峰） Friday, Sept 16 Meeting Room: Pavillion Vert " Green Temple" (near the Department of Physics, University of Fribourg) Session 1, Chaired by Yi-Cheng Zhang 14:00 – 14:30, Yi-Cheng Zhang: Welcome 14:30 – 18:00, Plenary Talks Hans Herrmann (ETHZ, Swiss Federal Institute of Technology Zurich): Physics of Sand dunes and beyond Dott. Giulio Cimini （ Uni Fribourg and Univ. Rome, Italy ）： Newsbag, an adaptive model for news recommendation Jian-Wei Zhang, (University of Hamburg), Potentials of sino-european cooperations in complexity sciences Sai-Ping Li, (Institute of Physics, Academia Sinica) TAIPEX------An Online Experimental Platform to Study Market Behavior 18:00-20:30, Welcoming Banquet Saturday, Sept 17 Meeting Room: Pavillion Vert " Green Temple" (near the Department of Physics, University of Fribourg) Session 2, Chaired by Jian-Wei Zhang 9:00 –10 :30. Plenary Talks Xu Cai （ CCNU ） : Conspectus on complexity science Researc Bing-Hong Wang (USTC): Perspectives of several directions in recent complex system research Yu-Gang Ma （ SIAP ）： Critical point and critical cluster distribution of explosive site percolation in random network Jian Jiang（ CCNU ）： Long division unites - long union divides, A model for cultural evolution Jiao Gu （ Central China Normal University ， Wuhan ， P.R.China ） The spectral analysis for biology networks 10:30-11:00: Coffee Break 11:00-12:00: Plenary Talks: You-Gui Wang (BNU) ： Self-organization and Preconditions of Efficient Markets Qinghua Chen （ BNU ）： Statistics and Evolution of Donations for 2008 Wenchuan Earthquake Jiang Zhang （ BNU ）： Accelerating growth and size-dependent distribution of human online activities 12:00-1 4:30: Lunch Session 3 Chaired by Bing-Hong Wang 14:30-16:00, Plenary Talks Yan Gao (USST) ： Piecewise Smooth Lyapunov Function for a Nonlinear Dynamical System Xing-Ye Li （ USST ） : Global Compact Representation of Continuous Piecewise Linear Functions and Its Applicatio Hui-Jie Yang （ USST ）： Hurst Exponents for Short Time Series Ding-Ding Han （ ECNU ）： Fluctuation scaling in complex networks Zike Zhang (Fribourg U) ： Statistical Mechanics of Social Tagging Networks: Structure, Dynamics and Function 16:00-16:30: Coffee Break 16:30-18:00: Plenary Talks: Dott. Stanislao Gualdi （ Uni Fribourg and Univ. Rome, Italy ）： A genetic perspective on citation networks Jeff Johnson, (Open University, London, UK) European and China cooperation opportunities in Complexity Sciences Fred von Gunten （ ISC, Uni Fribourg ） Complexity of systems with respect to the economy and society Yi-Cheng Zhang （ Fribourg U ）： Summary and Conclusion Remarks 18:00-19:30: Dinner Sunday, Sept 18 Travelling to Lausanne( 洛桑 ) and Geneva（日内瓦） Monday, Sept 19 l NESS Cooperation Session, Chaired by Yi-Cheng Zhang 9:00-10:30, Discussion and Talks: Yi-Cheng Zhang, (University of Fribourg) Yougui Wang （ BNU ） Paul Ormerod, (Volterra consulting) Bridget Rosewell, (Volterra consulting) Luciano Pietronero ， （ University of Rome ） Andrzej Nowak ， （ University of Warsaw ） David Hall ，（ Open University ） Danial Stauffacher ， President of The ICT For Peace Foundation 10:30-11:00: Coffee Break 11:00-11:30: Discussion and Closing Proceedings and post-event paperwork : Wei Han ， UESTC, Chengdu, China Tang Yong ， UESTC, Chengdu, China Li Chuncheng ， UESTC, Chengdu, China
标签: EU-China
