Study Of Individuals' Decision-making And Population Dynamic Evolution In Complex Interactive Environment

Nowadays, the environment of decision-making becomes more and more complicated, and the effect of information interaction and psychology on individuals' decision-making should not be ingored. Under this background, this paper mainly studies how does individuals'attributes such as preference, learning speed and emotion, and the external factors such as information interaction to influence individuals'decision-making and the population dynamic evolution. In order to study the individual's decision and population dynamics under complex environment from the perspective of cognitive science, we carry out the analysis of this paper as follows:First, we study the information interaction of participants in PDG and their strategy selection. With the development of the behavioral economics, more and more scholars put focus on the impact of psychological factors on decision-making. Some of them considered the effect of memory on individual's cooperation in PDG, and some of them studied the impact of interia on cooperation. In addition, the fraternal preference, the fairness preference and the jealous preference have been analyzed in the studies of individual's cooperation on PDG. All of these studies have provided a new perspective and ideas for us to study the cooperation on PDG. However, there were rare papers which studied the impact of individual's cognitive heterogeneity on his decision-making, and the features of individual's information interaction and decision-making under the complex environment. In order to understand the cooperation widespread in social system and ecological system from the perspective of cognitive science, we use the dual-process theory to explain the effect of individuals'information process mode on their physiological feedback and the behavior. In addition, we explore the dual-process theory to analyze the interaction mechanism of information and the selection of strategy of participants in PDG. Our study can enrich the studies of strategy selection and provide an explanation for the emergency of cooperation from the perspective of cognitive science.Second, we study the information interaction and decision-making in PDG. In which case does the individual prefer to cooperate with each other rather than competition merely? Why do people choose to cooperate? Which behavior can lure individual's socially advantageous behavior? In order to answer this question, in this paper we introduce the logic of appropriateness theory.This theory can not only guide people to focus the core mechanism in PDG, but also help people to identify the predictable source of variation, thus successfully explain the different results in similar condition.We put forward a decision framework base on the logic of appropriateness theory proposed by March (1994),and apply it to the field of decision-making in social dilemma. Our work can provide a new viewpoint to understand the decision-making in social dilemma.Third, we study the effect of information interaction on bidding strategy in combinatorial auctions. We use the latent variables interaction method to analyze the effect of information interaction on bidding strategy under the complex environment. The information includes these between the heterogeneous participants, and these between the bidders and the environment. We classify the information between the heterogeneous participants as follows:the ability of competitor, the motivation for bidding of competitor, the evaluation of competitor and the bidding experience of competitor. Meanwhile, we classify the information between the bidders and the environment as follows:the competitive degree of bidding, and the market evaluation of the auction target. Study the effect of information interaction on bidding strategy in the auction market can help mechanism-designer lure the bidding strategy of bidders to tell the true.Forth, we study the relationship between individual's learning speed and the population dynamic equilibrium in the emission permits market. The bidding strategies of participants in the emission permits market are not only influenced by their bidding experience, their comprehensive strength and their learning speed, but also impacted by the relative information of their competitor in the market. In fact, the exchange of information between the participants in the emission permits market is not unhindered. Some manufacturers can exchange their information with each other, while other manufacturers cannot do it. As a result, we use the complex networks to describe the system structure which is quite complicated, and study the impact of the complex environment in the emission permits market on the bidding strategies of the manufacturers. Then, by taking the learning speed of the manufacturers into consideration, we observe the impact of population structure and individual attribute on the evolution of bidding strategy and thus reveal the system evolution and the population behaviors.Fifth, we study the relationship between individual emotion and the population dynamic equilibrium in the regional electricity market. In order to study the bidding strategy evolution of generation company in the regional electricity market, we introduce the BA networks into the bidding games of generation companies to describe the structure of information interaction of the generation companies in the regional electricity market. Our study avoids the limitations of previous studies on "well-mixed" hypothesis, and reflects the effect of complex interactive environment, the information interaction structure and the degree of closeness between generation companies on their bidding strategy. At the same time, we introduce the over-confidence factor into the strategy updating rule, which can help us to understand the effect of generation companies'emotion factors on their strategy selection.Sixth, study the relationship between the individuals'preference and the population dynamic evolution in the co-competition of the supply chain system. The strategies of games on the supply chain can be classified roughly into two:one is cooperation, and the other is noncooperation, or defection. When cooperation can bring double-win, the supply chain enterprises will constraint and regulate their cooperation behaviors by bargaining or enter into contracts. When the conflict of interest occurs, the supply chain enterprises will give up the cooperate strategy. As a result, the enterprises in the supply chain market have to find a balance between the individual rationality and the collective rationality. We introduce the system dynamics theory into the replication dynamic system of the supply chain co-competition evolutionary game, and take the variable flow rate as root, and the flow-bit variable as the tail, then manipulate the flow rate variables through flow-bit variables and constants.In addition, we establish a basic model of the flow rate into the tree to simulate the dynamic process of the evo-game system. Taking the effect of individual's preference on the population dynamic, we introduce the interia factor of enterprises in the supply chain market and observe the effect mechanism of the interia level on their strategy selection and updating.The innovations of this paper are as follows:First, we use the dual-process theory and the logic of appropriateness theory to analyze the impact of information interaction on decision-making, Respectively. On the one hand, we use the dual-process theory,one of the psychological decision-making theories, to study the mechanism of information interaction and strategy selection in PDG, and explain how does the information process mode affect their psychological feedback and behavioral response in the social dilemma, thus explain the cooperation widespread in social and ecological systems from the perspective of cognitive science. On the other hand, we establish a decision-making frame based on the logic of appropriateness theory proposed by March (1994),and apply it into the decision-making in social dilemma, which can provide a new approach to solve the social dilemma.Second, we employ the latent variables interaction method to analyze the effect of information interaction on bidding strategy under the complicated environment. The information is classified into two dimensions:one is the information between the heterogeneous participants, and the other is the information between bidders and environment. By studying the effect of information interaction on bidding strategy in the auction market, the mechanism-designer can take full advantage of the information in the auction market and improve their auction mechanism, thus lure the bidding strategy of bidders to tell the true. This can be helpful to promote the trading efficiency and optimize the distribution of resource in the auction market.Third, we take the emission permits market and the power market for example, and use the complex networks to portray the complicated decision-making environment and information interaction structure. Taking the individual's heterogeneity, preference and emotion into consideration, we take the emission permits market, the power market and the supply chain co-competition system for example, and study the effect mechanism of individuals'attributes such as the learning speed, the over-confidence and the interia on their strategy selection, as well as the evolution of the population dynamic equilibrium.The inadequacies of this paper are as follows:On the one hand, we use the complex networks such as the small-world networks and the scale-free networks to describe the real networks, such as the emission permits market and the power market.However, although these real networks have several characters of complex networks to a certain degree, there are still many difference between the theoretical networks and the real ones.On the other hand, when we analyze the evolution of individuals' decision-making and the population dynamic equilibrium, the strategy set is assumed as two-strategies in all social games. This is for the simplicity in the mathematical derivation. However, the strategies of individuals in the real world are not limited to two-strategy.As a result, our research in the future are establishing the highly-consistent networks structure of the real systems by data collection and processing,and taking the multi-strategy into consideration. Our research can provide several decision supports for the government and relevant departments.