Research On Modeling Socio-Economic Systems Based On Theories Of Complex Network And Evolutionary Game

Some important issues for the study of complex systems are analyzing and modeling the structure and the dynamics of socio-economic systems. Recently, with the rise of the study of complex networks, networks in both nature and human societies, whose structure is irregular, complex and dynamically evolving in time, attract great research interest. A lot of analyses show that social and economic networks from the real world exhibit rich structure characteristics of complex networks, thereby providing new empirical foundations for modeling socio-economic systems. Evolutionary game theory focuses on modeling and analyzing the dynamics of the evolution of cooperation using methods of mathematical modeling, computer simulation, etc. Socio-economic systems are characteristic of extensive cooperation and it is of important theoretical significance and guiding function for solving real problems to apply evolutionary game theory to studying the evolution of cooperation in these systems. Though fruitful results have been achieved in this area, there are still many questions due to the complexity of socio-economic systems, such as the influences of_complex network structure, diverse human behaviors, and other factors.Based on theories of complex network and evolutionary game, this dissertation focuses on socio-economic systems and studies two central topics, i.e. their structure represented by networks and their dynamics of the evolution of cooperation, synthetically using methods of multiple disciplines, such as graph theory, differential equation, Agent-based simulation, etc. On one hand, this dissertation studies how to model large-scale social networks with community structure and proposes a new network model with community structure; on the other hand, this dissertation studies how to model the dynamics of the evolution of cooperation in socio-economic systems, by investigating the effects of diverse human behaviors, strategy update rules, complex network structure, following the research path from evolutionary games with other human behaviors (no network structure) to evolutionary games on regular networks and evolutionary games on complex networks. The main results and contributions of this dissertation are as follows.1. A social network model with community structure is proposed and the corresponding algorithm is provided. How to model large social networks with community structure is studied in this dissertation. By considering the sociality of nodes in social networks, social distance is defined and the mechanisms of linking via social similarity and triad formation are added into B-A scale-free network model. Both numeric analysis and simulation show that this network model not only maintains the property of scale-free degree distribution, but it has tunable strength of community structure and clustering coefficient.2. The effect of redistribution behaviors upon the evolution of cooperation in evolutionary game dynamics is investigated. Inspired by recent advancement in the interdisciplinary study of human behaviors, the general behavior of redistribution is introduced into the basic model of evolutionary game and a two-stage co-evolutionary model is formed. As an example, the co-evolutionary model with public goods game is analyzed using both methods of population dynamics and Agent-based dynamics. The approach to achieve stable equilibrium with a certain proportion of cooperation for the systems is presented and the influence of redistribution behaviors on the evolution of cooperation is revealed.3. The different results for evolutionary games on regular networks caused by different strategy update rules are studied. By considering the classification of strategy update rules, synchronization proportion and threshold proportion are defined to describe synchronization rules and threshold rules, respectively. By simulating the evolution of cooperation on regular lattice, it is found that selection rules have a great effect upon the range of cost-to-benefit ratio for cooperation. Generally, threshold selection rule enlarges the range of cost-to-benefit ratio for cooperation in the processes of evolutionary games on networks.4. Evolutionary games on R-B hierarchical network model are studied and a way of modifying the model to increase cooperation level is presented. To study the influence of structure characteristics on cooperation in evolutionary game dynamics, the dynamics of evolutionary games on R-B model is simulated. By comparing the result of R-B model with that of B-A model, it is verified that interconnection between hub nodes is one factor for high-level and robust cooperation in evolutionary games on complex networks. R-B model is modified by interconnecting a few hub nodes and basic statistical characteristics of hierarchical networks are maintained. After simulating the dynamics of evolutionary games on modified R-B model, it is found that cooperation level increases.