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1.
Margo Bergman 《Complexity》2004,9(5):25-30
The existence of risky choices makes the study of attitudes toward risk important. In this article we ask the following questions: Do risk‐neutral preferences maximize utility? Are there other measures of social welfare that can explain risk aversion in society? What effect does evolution have on the distribution of risk attitudes and the measures of social welfare? In a static environment risk‐neutral risk attitudes maximize utilitarian measures of social welfare, and risk‐averse attitudes maximize Rawlsian measures. In a dynamic system agents will tend toward risk, preferring greater affinity for risk when they can accumulate wealth. © 2004 Wiley Periodicals, Inc. Complexity 9: 25–30, 2004 相似文献
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开源软件由开源社区内的成员自发参与并协同完成开发,是一种高效的、有别于传统的软件生产模式。开源社区的主要成员有软件用户及开源软件服务提供商。本文通过构建三阶段模型,研究了服务提供商的市场策略及开源社区内用户创新对服务提供商参与策略的影响。研究发现:(1)若市场上高价值用户较少,服务提供商应采取低质量、低价格的市场策略,否则应采取高质量、高价格策略。(2)服务提供商要避免搭便车行为,即为了增加服务利润,它必须投入资源参与开源社区、提高软件质量。(3)当服务市场上目标用户较多且开源社区内用户参与动机较强时,服务提供商应采取高参与策略,否则采取低参与策略。本文的研究对服务提供商如何利用和参与开源社区具有指导意义。 相似文献
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We present an agent‐based model of bicycle racing that incorporates both physiology and the types of multiplayer scenarios that arise in real races. In these scenarios, riders can choose to share the workload with other riders (cooperate) or pursue their own self‐interests (defect). We compare the model's predictions to race situations and use it to investigate how different strategies can affect outcomes. We find that an individual player's best strategy depends on fitness level: below‐average riders fare better as defectors whereas above‐average riders perform better as cooperators. The strategies of stronger riders affect their teammates' results as well. The teammates of defecting strong riders fare worse overall than the teammates of cooperating strong riders. These results reproduce a dynamic that played out in the 2009 Tour de France. The winner, Alberto Contador, pursued a strategy perceived by many to be unusually uncooperative by repeatedly defecting on his teammates. The strategy worked to his advantage but may have negatively affected his teammates' placements. © 2011 Wiley Periodicals, Inc. Complexity, 17,39–44, 2011 相似文献
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We propose a simple model of first impression bias (FIB), where agents tend to ignore features which contradict their initial view. We consider a population of agents which are all in contact with a media, communicating randomly chosen features of an object. In some cases, we observe on simulations that FIB is significantly more frequent when the agents interact with each other than when they are only in contact with the media. We design an analytical aggregated model of the global agent‐based model behavior, which helps to explain the higher number of FIB due to the interactions. © 2009 Wiley Periodicals, Inc. Complexity, 2010 相似文献
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Burton Voorhees 《Complexity》2006,11(3):44-57
Two simple models of emergence and automated induction are described. In the first, an initially random process comes, over time, to emulate a deterministic process with noise. In the second, an induction algorithm is used to make unbiased best guess estimates of cellular automata rules generating a given time series of binary strings. The general conclusions are as follows: (1) that it may not be possible to distinguish between a stochastic process with selection and reinforcement and a noisy deterministic process; and (2) automated induction algorithms will often be vulnerable to errors of type 1 when faced with random data. In this second case, this leads to a method for study of the modeling class assumed in the induction algorithm. © 2006 Wiley Periodicals, Inc. Complexity 11: 44–57, 2006 相似文献
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We report computer simulation experiments based on our agent‐based simulation tool to model the multiperson Chicken dilemma game for the case when the agents are greedy simpletons who imitate the action of that of their neighbors who received the highest payoff for its previous action. The individual agents may cooperate with each other for the collective interest or may defect, i.e., pursue their selfish interests only. After a certain number of iterations the proportion of cooperators stabilizes to either a constant value or oscillates around such a value. The payoff (reward/penalty) functions are given as two straight lines: one for the cooperators and another for the defectors. The payoff curves are functions of the ratio of cooperators to the total number of agents. Even for linear payoff functions, we have four free parameters that determine the payoff functions that have the following properties: (1) Both payoff functions increase with the increasing number of cooperators. (2) In the region of low cooperation the cooperators have a higher reward than the defectors. (3) When the cooperation rate is high, there is a higher payoff for defecting behavior than for cooperating behavior. (4) As a consequence, the slope of the D function is greater than that of the C function and the two payoff functions intersect. (5) All agents receive a lower payoff if all defect than if all cooperate. We have investigated the behavior of the agents systematically. The results show that the solutions have predictable tendencies but they are nontrivial and quite irregular. The solutions show drastic changes in the parameter ranges 0.6 ≤ R ≤ 0.65 for all values of S and 0 ≤ S ≤ 0.2 when R < 0.6 (R is the reward for mutual cooperation and S is the sucker's payoff to a lonely cooperator). © 2010 Wiley Periodicals, Inc. Complexity, 2010 相似文献
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We investigated dynamics of group decision making on complex problems when agents can form mental models of others from discussion history. Results indicated that as the agents' memory capacity increases, the group reaches superficial consensus more easily. Surprisingly, however, the shared mental model of the problem develops only within a limited area of the problem space, because incorporating knowledge from others into one's own knowledge quickly creates local agreement on where relevant solutions are, leaving other potentially useful solutions beyond the scope of discussion. The mechanisms stifling group‐level exploration and their implications for decision making research are discussed. © 2010 Wiley Periodicals, Inc. Complexity 16: 49–57, 2011 相似文献
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We develop a computational model to explore how ethnic geography shapes the distribution of violence in civil war. We seed the model with disaggregated data on ethnic settlement patterns in Afghanistan and calibrate the model parameters to fit empirically observed locations of violence against civilians. Our simulation suggests that (i) political actors are more likely to attack civilians in heterogeneous areas where members of one ethnic group are exposed to members of a rival group; (ii) violence directed at civilians occurs with greater frequency in locations where one political actor exercises hegemonic but incomplete territorial control (relative to areas of complete or mixed control); and (iii) geographically concentrated ethnic minorities face a higher risk of violence. © 2012 Wiley Periodicals, Inc. Complexity, 2012 相似文献
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Michael J. North Charles M. Macal James St. Aubin Prakash Thimmapuram Mark Bragen June Hahn James Karr Nancy Brigham Mark E. Lacy Delaine Hampton 《Complexity》2010,15(5):37-47
Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression‐based models, logit models, and theoretical market‐level models, such as the NBD‐Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method—agent‐based modeling—shows promise for addressing these issues. Agent‐based models use business‐driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system‐level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent‐based modeling to develop a multi‐scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings. © 2010 Wiley Periodicals, Inc. Complexity, 2010 相似文献
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This study discusses the evolutionary nature of knowledge acquisition at micro and macro levels, and in particular when the process involves an artificial agent's interpretative devices. In order to accomplish this, we propose using an individual learning model (or inner‐world reconstruction model) that in our view overcomes neoclassic epistemological holdups and may increase the predictive power of computational economics, by letting an artificial agent's knowledge evolve by itself, irrespective of globally specified goals or individual motives of behavior; using simultaneous (or parallel) genetic algorithms (GA) to evolve a single agent's learning strategy, each GA with different general specifications, in a multiagent setting. © 2006 Wiley Periodicals, Inc. Complexity 11: 12–19, 2006 相似文献
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采用广义溢出指数法对2011年至2017年我国股票、期货及债券三个市场之间的信息溢出机制进行了研究,结果发现:股市对期市和债市均有收益率溢出影响,而股市和期市对债市均有波动率溢出影响;三个市场的整体溢出指数值偏低,表明我国不同资产市场之间的关联性相对来说较小;时变特征也表明股市大多数情况处于溢出状态,期市方向不明确,债市则大多数情况处于被溢出状态;对溢出值的非对称检验发现,正向波动比负向波动的溢出值更大,但是统计上并不显著。对2015年6月股灾前后三个市场的波动率溢出情况进行分析后发现,股市的极端风险更容易向期市传染,而债市相对更为稳定,不容易被极端风险感染。 相似文献
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We report computer simulation experiments based on our agent‐based simulation tool to model a new N‐person game based on John Conway's Game of Life. The individual agents may choose between two behavior options: cooperation or defection. The payoff (reward/penalty) functions are given as two parabolas: one for each option. After a certain number of iterations, the behavior of the agents stabilizes to either a constant value or oscillates around such a value. The simulation's goal is to investigate the effects of intermediate behavior on a society of agents. We have performed a systematic investigation of this game for all six possible cases of the mutual positions of parabolic payoff functions crossing each other at two points: x = 0.3 and 0.7 where x is the ratio of the cooperation choice to the total number of agents in the agent's neighborhood. The global ratios X(t) of the total number of cooperators in the entire array of agents as functions of time (iterations) and the solutions of the game Xfinal as functions of X0 were observed for each case for Pavlovian, greedy, and conformist agents. The solutions have predictable tendencies only when the neighborhood is the entire array of greedy or conformist agents. In all other cases unexpected properties emerge. © 2009 Wiley Periodicals, Inc. Complexity, 2010 相似文献
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Andrew W. Bausch 《Complexity》2015,21(2):82-92
This article implements the spatial Prisoner's Dilemma (PD) as an agent‐based model. Many previous models have assumed that agents in a spatial PD interaction exclusively and deterministically within their von Neumann neighborhood. The model presented here introduces stochastic interactions within a subset of the von Neumann neighborhood. This implementation allows a direct comparison of the effect of stochastic interactions relative to deterministic interactions on the level of cooperation that emerges in the system. The results show that when holding the total number of interactions agents participate in each round constant, allowing agents to interact stochastically increases cooperation in the system relative to deterministic interactions. © 2014 Wiley Periodicals, Inc. Complexity 21: 82–92, 2015 相似文献
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近年来,利用复杂性科学解释人类行为成为一个新兴的研究热点.与以群体或群体中部分个体为研究对象不同,以codeplex开源软件社区所有个体知识创造行为为研究对象,利用人类行为动力学方法从活跃度、阵发性、时间间隔分布、长程相关性四个侧面对社区中所有个体知识创造过程中的生产行为、沟通行为、bug讨论行为进行分析.发现开源软件社区中生产者个体的这三种行为在活跃度、分布形式及分布参数、阵发性指标、长程相关性都呈现出显著的差异性.最后,对造成这种差异性的原因进行了讨论. 相似文献
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The objective of this paper is to pose and solve a simple class of coordinated motion problems that capture the following question; When is formation travel optimal? This class of problems is complementary to two related classes of problems that have received significant attention: close formation travel and the generation of flocking behavior. We pose and solve this problem for the case of two agents traversing a finite, connected graph. Two examples are provided, illustrating the application of the results. 相似文献
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An agent‐based C++ program was developed to model student drinking. Student‐agents interact with each other and are randomly subjected to good or bad drinking experiences, to stories of other students' experiences, and to peer pressure. The program outputs drinking rates as functions of time based on various input parameters. The intent of this project is to simulate alcohol use, eventually adding other drugs, and possibly creating a simulation game for use as an educational tool. © 2008 Wiley Periodicals, Inc. Complexity, 2009 相似文献
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Asynchronous Teams: Cooperation Schemes for Autonomous Agents 总被引：1，自引：0，他引：1
Experiments over a variety of optimization problems indicate that scale-effective convergence is an emergent behavior of certain computer-based agents, provided these agents are organized into an asynchronous team (A-Team). An A-Team is a problem-solving architecture in which the agents are autonomous and cooperate by modifying one another's trial solutions. These solutions circulate continually. Convergence is said to occur if and when a persistent solution appears. Convergence is said to be scale-effective if the quality of the persistent solution increases with the number of agents, and the speed of its appearance increases with the number of computers. This paper uses a traveling salesman problem to illustrate scale-effective behavior and develops Markov models that explain its occurrence in A-Teams, particularly, how autonomous agents, without strategic planning or centralized coordination, can converge to solutions of arbitrarily high quality. The models also perdict two properties that remain to be experimentally confirmed: construction and destruction are dual processes. In other words, adept destruction can compensate for inept construction in an A-Team, and vice-versa. (Construction refers to the process of creating or changing solutions, destruction, to the process of erasing solutions.) solution quality is independent of agent-phylum. In other words, A-Teams provide an organizational framework in which humans and autonomous mechanical agents can cooperate effectively. 相似文献
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In this article, we present a multiagent system (MAS) simulation of a financial market and investigate the requirements to obtain realistic data. The model consists of autonomous, interactive agents that buy stock on a financial market. Transaction decisions are based on a number of individual and collective elements, the former being risk aversion and a set of decision rules reflecting their anticipation of the future evolution of prices and dividends and the latter the information arriving on the market influencing the decision making process of each trader. We specifically look at this process and the following observations hold: The market behavior is determined by the information arriving at the market and agent heterogeneity is required in order to obtain the right statistical properties of the price and return time series. The observed results are not sensitive to changes in the parameter values. © 2003 Wiley Periodicals, Inc. 相似文献
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