Research On Evolutionary Agent-based Artificial Social System Modeling Methods And Application

As the21st-centurys science, the complexity science is a new interdisciplinary discipline, and has become a main research direction of modern system science. As a tool for the complex system research, the modeling and simulation method of complex system is still at the stage of exploring, has not formed an integrated system, so it is necessary to be further studied. Firstly, based on complex adaptive system theory, evolutionary algorithm and artificial social method, a modeling method for artificial social system, called evolutionary agent-based artificial social system modeling method, is constructed in the dissertation. Secondly, taking enterprise system as application background, combining with the principles of microeconomics and complex network theory, utilizing the established evolutionary agent-based artificial social system modeling method, we establish the enterprise evolution model and the enterprise relationship network evolution model based on the evolutionary agent. The main achievements are obtained as follows:1. The evolutionary agent-based artificial social system modeling method is proposed. According to complex adaptive system theory and artificial social idea, by using the multi-agent modeling, depending on the local details of individual in artificial social system, the right evolutionary algorithms is applied in the agent’s reaction rules and various local behaviors, so the agent’s similar biological evolution and behavior optimization are implemented, a high intelligent and high adaptability micro agent structure and model is constructed. Moreover, the evolutionary agent-based artificial social system modeling method is formed by applying the established evolutionary agent model. Finally, the difficulties and the characteristics of the model are analyzed.2. The evolutionary agent-based enterprise evolutionary model is constructed. Towards the evolution process of enterprise system, by applying the evolutionary agent-based artificial social system modeling method, analyzing the characteristics of the behavioral agents, the appropriate evolutionary algorithms is selected to establish the basic structure of the enterprise system, the micro adaptive agents model, the overall macro Echo model, respectively, and the evolutionary agent-based enterprise organization evolutionary model. In order to show the validity of the method, the simulation is performed in the SWARM platform, the evolutionary relations between micro-agents behaviros and macro-complex phenomena are observed, some complex adaptive behaviors of enterprise organization are discussed. 3. The member behavior parameters optimization model based on improved particle swarm algorithm is constructed. According to the micro-agents adaptive behaviors in the enterprise organization system, the particle swarm optimization algorithm with constraint-preserving mechanism(CPPSO) is applied to solve the member behavior parameters optimization problems. Depending on the demand preference and the productivity of member, a member behavior parameters optimization model based on the improved particle swarm algorithm in order to maximize the utility of member. Furthemore, the optimization model is applied in the evolutionary agent-based enterprise evolution model, the simulation results shows that under the actual demand and constraint conditions, the use of CPPSO algorithm can obtain the global optimal solution fairly quickly, greatly improve the learning ability of member, and reflect the difference between the ideal benefit and the practical benefit of member effectively.4. The evolution of resource agents based on genetic algorithm is implemented. Firstly, based on the properties of resource agents, agent is encoded with real-number. Secondly, by analyzing the relationship between the resource agents and the resource’s value, the member’s demand, the fitness function is designed. Then, according to the evolutionary laws of survival of the fittest of genetic algorithm, the evolution of resource agents using genetic operations is presented. Through the simulation, the evolutionary mechanism of resource agents is realized in the evolutionary agent-based enterprise evolution model. In addition, the effect of the resource evolution on the evolution process of enterprise organization is analyzed in detail.5. The enterprise relationship network model based on evolutionary agent is constructed. According to the characteristics of agent behaviors, the evolutionary agents’behavior strategies are designed, the intelligent agent nodes are presented. Accompanying the enterprise organization evolutions, the connection between agent nodes are gradually established, and the enterprise relationship network model is gradually formed. Through the simulation, the generation and evolution of enterprise relationship network model are presented, moreover, the evolution laws of enterprise relationship network are analyzed using the statistic characteristics of complex networks. The simulation results show that enterprise relationship network is gradually generated and evolved during the process of the agent nodes searching for resources, the network structure is constantly evolving with the enterprise evolutions, finally, the complex networks with the small-world and scale-free characteristic is formed.