基于计算机试验的进化博弈研究

采用理论分析与计算机试验的方法研究一类常见的社会悖论问题———重复多人囚犯博弈问题.用随机试验方法对局中人的各种博弈法则进行分析比较,研究支付函数与博弈环境对各博弈法则性能指标的影响.并以进化博弈的观点,讨论在长期的重复博弈过程中,博弈法则进化到某种稳定状态的情况.     

局部凸H-空间内非紧无限最优化和约束对策

应用局部凸Ｈ－空间内具有闭零调值的上半连续集值映象的Ｆａｎ－Ｇｌｉｃｋｓｂｅｒｇ型不动点定理和极大化定理,对无限最优化总理２和约束对策问题在没有线性结构的局部凸Ｈ－空间内证明了解的某些新的存在定理,这些定理改进和推广了最近文献中的许多重要结果。     

局部G-凸空间内的广义矢量拟平衡问题

在局部G-凸空间内引入和研究了几类广义矢量拟平衡问题(GVQEP)．包含了大多数广义矢量平衡问题,广义矢量变分不等式问题,拟平衡问题和拟变分不等式问题作为特殊情形．首先在局部G-凸空间内对一人对策证明了一个平衡存在性定理．作为应用,在非紧局部G-凸空间内对GVQEP的解建立了某些新的存在定理．这些结果和论证方法与最近文献中的结果和论证方法相比较是新的和完全不同的．     

Stability and Evolution of Synonyms and Homonyms in Signaling Game

Synonyms and homonyms appear in all natural languages. We analyze their evolution within the framework of the signaling game. Agents in our model use reinforcement learning, where probabilities of selection of a communicated word or of its interpretation depend on weights equal to the number of accumulated successful communications. When the probabilities increase linearly with weights, synonyms appear to be very stable and homonyms decline relatively fast. Such behavior seems to be at odds with linguistic observations. A better agreement is obtained when probabilities increase faster than linearly with weights. Our results may suggest that a certain positive feedback, the so-called Metcalfe’s Law, possibly drives some linguistic processes. Evolution of synonyms and homonyms in our model can be approximately described using a certain nonlinear urn model.     

The minority game with incomplete strategies

This paper proposes a new model of Incomplete Minority Game (IMG), which features a default hierarchy of rules. This model introduces random bits into players’ individual strategies and is capable of applying the exception rules in the absence of the default one. Analysis of the numerical experiment results indicates that, in comparison with the standard Minority Game (SMG) model, this IMG model expands the maximum ensemble of uncorrelated strategies (MEUS) and excels in the effective strategy set and dynamic evolution of individual strategies, which enhance the overall performance by reaching an approximate ideal status in a shorter time with less memory steps and more stable combination of strategies. This paper also discusses the practical implication of the new IMG model.     

Costly punishment and cooperation in the evolutionary snowdrift game

The role of punishments in promoting cooperation is an important issue. We incorporate costly punishments into the snowdrift game (SG) by introducing a third punishing (P) character, and study the effects. The punishers, who carry basically a cooperative (C) character, are willing to pay a cost α so as to punish a non-cooperative (D) opponent by β. Depending on the initial fractions of the characters, α, β, and the cost-to-benefit ratio r in the SG, the three-character system evolves into a steady state consisting either only of C and P characters or only of C and D characters, in a well-mixed population. The former situation represents an enhancement in cooperation relative to the SG, while the latter is similar to the SG. The dynamics in approaching these different steady states are found to be different. Analytically, the key features in the dynamics and the steady states observed in simulations are captured by a set of differential equations. The sensitivity to the initial distribution of characters is studied by depicting the flow in a phase portrait and analyzing the nature of fixed points. The analysis also shows the role of P-character agents in preventing a system from invasion by D-character agents. Starting from a population consisting only of C and P agents, a D-character agent intended to invade the system cannot survive when the initial fraction of P agents is greater than r/β. Our model, defined intentionally as a simulation algorithm, can be readily generalized to incorporate many interesting effects, such as those in a networked population.     

The design of a Tort law to control accidents

In this paper we analyse a two-stage game involving the government and n agents who engage in a single activity (driving). The government establishes the legal policy setting and the agents proceed to play a non-cooperative game of incomplete information with a risk of accident in which their behavioral strategy is their level of care. We examine the Nash-equilibrium conditions for single-activity accidents between heterogeneous agents, ‘good’ drivers or ‘bad’ drivers allowing a variable damage function and a liability rule defined on the cube. The relative desirability for society of alternative equilibria and the conditions under which they can obtain are discussed. The constraints which circumscribe the ability of the government to induce an equilibrium involving careful driving are demonstrated. It transpires that when the proportion of good drivers increases, it becomes more difficult to sustain a careful equilibrium whereas an equilibrium of reckless behavior becomes easier to sustain. Various extensions of the models are also presented.     

The safer chemical design game. Gamification of green chemistry and safer chemical design concepts for high school and undergraduate students

Green chemistry can strongly attract students to chemistry. We, therefore, developed a green chemistry educational game that motivates students at the undergraduate and advanced high school levels to consider green chemistry and sustainability concerns as they design a hypothetical, chemical product. The game is intended for incorporation into any chemistry course for majors and non-majors that teaches sustainability and/or the Principles of Green Chemistry at the undergraduate level. The game is free of charge and encourages students to think like professional chemical designers and to develop a chemical product with respect to function and improved human and environmental health. This computer simulation has been assessed by educators and can be seamlessly integrated into an existing curriculum.     

基于熵值Topsis和博弈动力学的空港联盟决策研究

针对空港在面临联盟选择时的决策问题进行了研究,认为众空港在博弈中的收益为不等值,从区域发展、生产要素、需求状况、支撑产业和环境影响五方面建立空港联盟收益的指标体系,将空港网络抽象成小世界网络,结合熵值Topsis和小世界网络博弈动力学建立空港联盟决策算法,并且运用2010年我国25大空港的实证数据进行研究。结论显示空港联盟只能解决空港发展的一时问题,提升自身能力才是重中之重,研究结论具有实际应用意义。     

Computing approximate Nash equilibria in general network revenue management games

Computing optimal capacity allocations in network revenue management is computationally hard. The problem of computing exact Nash equilibria in non-zero-sum games is computationally hard, too. We present a fast heuristic that, in case it cannot converge to an exact Nash equilibrium, computes an approximation to it in general network revenue management problems under competition. We also investigate the question whether it is worth taking competition into account when making (network) capacity allocation decisions. Computational results show that the payoffs in the approximate equilibria are very close to those in exact ones. Taking competition into account never leads to a lower revenue than ignoring competition, no matter what the competitor does. Since we apply linear continuous models, computation time is very short.