Other affiliations: Shenzhen Stock Exchange
Bio: Hedong Xu is an academic researcher from Jinan University. The author has contributed to research in topics: Stochastic game & Monopoly. The author has an hindex of 6, co-authored 12 publications receiving 92 citations. Previous affiliations of Hedong Xu include Shenzhen Stock Exchange.
TL;DR: A memory-based stag hunt game is proposed, and it is found that the memory length M will promote the cooperation level and the larger the memorylength is, the higher the cooperationlevel will be.
Abstract: Memory normally plays an important role when people make a decision. Thus, it is reasonable and necessary to introduce the influence of memory in the evolutionary game theory. However, the previous work mainly focuses on prisoner’s dilemma, snowdrift game or public good game, but little on stag hunt game. In this paper, a memory-based stag hunt game is proposed. For each iteration, the players in the regular lattices will first choose its neighbor who has the largest accumulated payoff in the last M runs. Then, according to the Femi rule, the player will determine whether learning from the neighbor or not. It is found that the memory length M will promote the cooperation level. The larger the memory length is, the higher the cooperation level will be. Furthermore, when the payoff parameter is less than 0.75, cooperation will always spread the whole regular lattices. As the parameter is larger than 0.75, no matter how large the memory length is, the behavior of defection will always exist. Our work may shed some new light on the study of evolutionary games with memory effect.
TL;DR: An investor sharing game is proposed, where investors’ payoffs relate to their investing amount and the degree of monopoly in the industry market, and the simulation on WS small-world networks shows that cooperative behaviors will prosper by the union of investors who invest less amounts in a less monopolized market.
Abstract: Investors often co-invest in the same project together As the payoff of the project realizes, how to share the total payoff is in consideration With this inspiration, an investor sharing game is proposed in this paper, where investors’ payoffs relate to their investing amount and the degree of monopoly in the industry market Economically, the degree of monopoly in the market is introduced in the game by a parameter α that affects the evolutionary process The distribution of investing amounts is assumed to satisfy the Pareto distribution in terms of the empirical wealth distribution The simulation on WS small-world networks shows that cooperative behaviors will prosper by the union of investors who invest less amounts in a less monopolized market The higher power of the Pareto distribution of investing amounts also results in more cooperators in equilibriums Furthermore, as the degree of monopoly swings, the density of cooperators is higher and more stable in a more random small-world network The findings may be helpful in understanding the effect of network structure on the emergence of cooperation
TL;DR: This work proposes an investors’ power-based game, where the payoffs of defectors depend on the efficiency of market and the related-power against cooperators, and shows that, an improvement of efficiency benefits for the cooperation fundamentally.
Abstract: The classical prisoner dilemma game on networks ignores the heterogeneity of players that may lead to the remarkable differences of their payoffs in reality. With the consideration of the heterogeneity, we propose an investors’ power-based game, where the payoffs of defectors depend on the efficiency of market and the related-power against cooperators. Economically, the efficiency of the market of investment is introduced in the game through a parameter α that becomes a key factor in the evolutionary process. Our simulation results show that, an improvement of efficiency benefits for the cooperation fundamentally. Furthermore, comparing with the result on BA scale-free networks, the evolution of cooperation performs great stability on WS small-world networks against the change of market efficiency. As the network of investment in real world may possess both of the properties of WS small-world networks and BA scale-free networks, the findings may be helpful in understanding and controlling the behaviors on the network of investment.
TL;DR: Effects of investors’ power correlations in the power-based game on networks are studied and theoretically show that the expected payoff of a cooperator is more than that of a defector as the level of assotativity is high enough, verifying the theoretical inference.
Abstract: With the consideration of the heterogeneity of investors, an investors’ power-based game is proposed (Xu et al., 2018), where payoffs of defectors depend on the efficiency of market and the related-power against cooperators. Directed by the special structure of the power-based game, effects of investors’ power correlations in the power-based game on networks are studied in this paper. The power correlations, also called the degree correlation in the traditional theory of graph, is usually measured by the assortativity coefficient r . Firstly, we theoretically show that the expected payoff of a cooperator is more than that of a defector as the level of assotativity is high enough. Meanwhile, our simulation results show that, an increment of assortativity coefficient raises the average payoffs of cooperators and boosts cooperations, verifying the theoretical inference. Furthermore, as the market efficiency α swings, the density of cooperators will be higher and more stable on the network with the larger r . As the network of investment in real world may possess both of the properties of BA scale-free networks and assortative networks, the findings may be helpful in managing the emergence of cooperative behaviors.
TL;DR: In this paper, the authors proposed the accumulated temptation game, where the temptation is of heterogeneity among agents according to historical strategies and the accumulation factor is introduced to measure the amplitude of the variation of temptations.
Abstract: The temptation in the traditional prisoner’s dilemma is constant. To explore the evolution of temptations, the accumulated temptation game is proposed, where the temporal temptation is of heterogeneity among agents according to historical strategies. Agents accumulate the temptations by cooperation but consume the temptation by defection. The accumulation factor is introduced to measure the amplitude of the variation of temptations. During the evolutionary process, the density of cooperators and the average temptation may move towards the same direction. Cooperative behaviors will be eliminated if the accumulation factor is large enough. As an interesting result, a fraction of agents may keep cooperation constantly for accumulating temptations and they instantaneously defect at a certain time. The higher accumulation factor accelerates the instantaneous defection of agents. The completely random networks play an essential role in motivating cooperation when the temptation is small.
TL;DR: Why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease are detailed.
Abstract: Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.
01 Jan 2012
TL;DR: The influence of institutional investors on myopic R＆D investment behavior was discussed by Bushee as discussed by the authors, who claimed that institutional investors had a profound influence on investment behavior.
Abstract: 机构投资者作为证券市场中的重要力量,越来越受到理论界和实务界的关注。论文对宾夕法尼亚大学沃顿商学院会计学教授布赖恩-布希（Brian Bushee）的论文＂The influence of institutional investors on myopic R＆D investment behavior＂（机构投资者对企业短视研发投资行为的影响,以下简称Bushee（1998））进行评价并提出相关的建议和研究方向。
01 Jan 1993
TL;DR: In this paper, the impacts of policy incentives and consumer preferences on electric vehicle charging infrastructures are analyzed to improve the economic efficiency while reducing the fiscal pressure of the government.
Abstract: Because of the fast-growing market share of electric vehicles, the need for charging facilities is growing rapidly. In order to promote the construction of electric vehicle charging infrastructures, the impacts of policy incentives and consumer preferences are analyzed. Balanced subsidy and taxation policies are employed in this paper to improve the economic efficiency while reducing the fiscal pressure of the government. From the aspect of the market, consumer preferences on electric vehicles are modeled in the paper by dividing consumers into three types. In response to the policy incentive, consumers can choose different types of mobility, i.e., electric vehicle or fuel vehicle. The time-varying needs of charging stations and fuel stations in each area are characterized by an evolutionary game model built in the framework of a small-world complex network considering the competitive connections between the stations. The results prove the advantages of the balanced dynamic subsidy and taxation policies on the promotion of electric charging infrastructures. It is noticed that the investment is not the main barrier for the deployment of charging stations. The penetration level of electric vehicles and charging prices are the main driving forces. The findings can provide certain references for policymakers and investment companies.
TL;DR: The present study introduces a wide-ranging reporting of nature- stimulated meta-heuristic methods, which are used throughout the graph coloring, and focuses on emphasizing the optimization algorithms to handle the GCP problems.
Abstract: Typically, Graph Coloring Problem (GCP) is one of the key features for graph stamping in graph theory. The general approach is to paint at least edges, vertices, or the surface of the graph with some colors. In the simplest case, a kind of coloring is preferable in which two vertices are not adjacent to the same color. Similarly, the two edges in the same joint should not have the same color. In addition, the same goes for the surface color of the graph. This is one of the NP-hard issues well studied in graph theory. Therefore, many different meta-heuristic techniques are presented to solve the problem and provide high performance. Seemingly, regardless of the importance of the nature-stimulated meta-heuristic methods to solve the GCP, there is not any inclusive report and detailed review about overviewing and investigating the crucial problems of the field. As a result, the present study introduces a wide-ranging reporting of nature- stimulated meta-heuristic methods, which are used throughout the graph coloring. The literature review contains a classification of significant techniques. This study mainly aims at emphasizing the optimization algorithms to handle the GCP problems. Furthermore, the advantages and disadvantages of the meta-heuristic algorithms in solving the GCP and their key issues are examined to offer more advanced meta-heuristic techniques in the future.