949 resultados para Nash-Equilibrium
Resumo:
The spatial dimension of agricultural production is important when a communicable disease enters a region. This paper considers two sorts of biosecurity risk that producers can seek to protect against. One concerns the risk of spread: that neighboring producers do not take due care in protecting against being infected by a disease already in the region. In this case, producer efforts substitute with those of near neighbors. For representative spatial production structures, we characterize Nash equilibrium protection levels and show how spatial production structure matters. The other sort of risk concerns entry: that producers do not take due care in preventing the disease from entering the region. In this case, producer heterogeneity has subtle effects on welfare loss due to strategic behavior. Efforts by producers complement, suggesting that interfarm communication will help to redress the problem.
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This article introduces a model of rationality that combines procedural utility over actions with consequential utility over payoffs. It applies the model to the Prisoners Dilemma and shows that empirically observed cooperative behaviors can be rationally explained by a procedural utility for cooperation. The model characterizes the situations in which cooperation emerges as a Nash equilibrium. When rational individuals are not solely concerned by the consequences of their behavior but also care for the process by which these consequences are obtained, there is no one single rational solution to a Prisoners Dilemma. Rational behavior depends on the payoffs at stake and on the procedural utility of individuals. In this manner, this model of procedural utility reflects how ethical considerations, social norms or emotions can transform a game of consequences.
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A model of directed search with a finite number of buyers and sellers is considered, where sellers compete in direct mechanisms. Buyer heterogeneity and Nash equilibrium results in perfect sorting. The restriction to complementary inputs, that the match value function Q is supermodular, in addition coordinates the sellers strategies. In that case, equilibrium implements positive assortative matching, which is efficient and consistent with the stable (cooperative equilibrium) outcome. This provides a non-cooperative and decentralizedsolution for the Assignment Game. Conversely, if buyers are identical, no such coordination is possible, and there is a continuum of equilibria, one of which exhibits price posting, another yields competition in auctions.
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Small sample properties are of fundamental interest when only limited data is avail-able. Exact inference is limited by constraints imposed by speci.c nonrandomizedtests and of course also by lack of more data. These e¤ects can be separated as we propose to evaluate a test by comparing its type II error to the minimal type II error among all tests for the given sample. Game theory is used to establish this minimal type II error, the associated randomized test is characterized as part of a Nash equilibrium of a .ctitious game against nature.We use this method to investigate sequential tests for the di¤erence between twomeans when outcomes are constrained to belong to a given bounded set. Tests ofinequality and of noninferiority are included. We .nd that inference in terms oftype II error based on a balanced sample cannot be improved by sequential sampling or even by observing counter factual evidence providing there is a reasonable gap between the hypotheses.
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This paper studies sequential auctions of licences to operate in amarket where those firms that obtain at least one licence then engage ina symmetric market game. I employ a new refinement of Nash equilibrium,the concept of {\sl Markovian recursively undominated equilibrium}.The unique solution satisfies the following properties: (i) when severalfirms own licences before the auction (incumbents), new entrants buylicences in each stage, and (ii) when there is no more than one incumbent,either the single firm preempts entry altogether or entry occurs inevery stage, depending on the parameter configuration.
Resumo:
This article introduces a model of rationality that combines procedural utility over actions with consequential utility over payoffs. It applies the model to the Prisoners Dilemma and shows that empirically observed cooperative behaviors can be rationally explained by a procedural utility for cooperation. The model characterizes the situations in which cooperation emerges as a Nash equilibrium. When rational individuals are not solely concerned by the consequences of their behavior but also care for the process by which these consequences are obtained, there is no one single rational solution to a Prisoners Dilemma. Rational behavior depends on the payoffs at stake and on the procedural utility of individuals. In this manner, this model of procedural utility reflects how ethical considerations, social norms or emotions can transform a game of consequences.
Resumo:
In this paper we provide a full characterization of the pure-strategyNash Equilibria for the p-Beauty Contest Game when we restrict player schoices to integer numbers. Opposed to the case of real number choices,equilibrium uniqueness may be lost depending on the value of p and thenumber of players: in particular, as p approaches 1 any symmetric profileconstitutes a Nash Equilibrium. We also show that any experimental p-BeautyContest Game can be associated to a game with the integer restriction andthus multiplicity of equilibria becomes an issue. Finally, we show thatin these games the iterated deletion of weakly dominated strategies maynot lead to a single outcome while the iterated best-reply process alwaysdoes (though the outcome obtained depends on the initial conditions).
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We run experiments on English Auctions where the bidders already own a part (toehold) ofthe good for sale. The theory predicts a very strong effect of even small toeholds, however wefind the effects are not so strong in the lab. We explain this by analyzing the flatness of thepayoff functions, which leads to relatively costless deviations from the equilibrium strategies.We find that a levels of reasoning model explains the results better than the Nash equilibrium.Moreover, we find that although big toeholds can be effective, the cost to acquire them mightbe higher than the strategic benefit they bring. Finally our results show that in general theseller s revenues fall when the playing field is uneven.
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The two essential features of a decentralized economy taken intoaccount are, first, that individual agents need some informationabout other agents in order to meet potential trading partners,which requires some communication or interaction between theseagents, and second, that in general agents will face tradinguncertainty. We consider trade in a homogeneous commodity. Firmsdecide upon their effective supplies, and may create their ownmarkets by sending information signals communicating theirwillingness to sell. Meeting of potential trading partners isarranged in the form of shopping by consumers. The questions to beconsidered are: How do firms compete in such markets? And what arethe properties of an equilibrium? We establish existenceconditions for a symmetric Nash equilibrium in the firms'strategies, and analyze its characteristics. The developedframework appears to lend itself well to study many typicalphenomena of decentralized economies, such as the emergence ofcentral markets, the role of middlemen, and price-making.
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I study monotonicity and uniqueness of the equilibrium strategies in a two-person first price auction with affiliated signals. I show thatwhen the game is symmetric there is a unique Nash equilibrium thatsatisfies a regularity condition requiring that the equilibrium strategies be{\sl piecewise monotone}. Moreover, when the signals are discrete-valued, the equilibrium is unique. The central part of the proof consists of showing that at any regular equilibrium the bidders' strategies must be monotone increasing within the support of winning bids. The monotonicity result derived in this paper provides the missing link for the analysis of uniqueness in two-person first price auctions. Importantly, this result extends to asymmetric auctions.
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This paper studies the equilibrating process of several implementationmechanisms using naive adaptive dynamics. We show that the dynamics convergeand are stable, for the canonical mechanism of implementation in Nash equilibrium.In this way we cast some doubt on the criticism of ``complexity'' commonlyused against this mechanism. For mechanisms that use more refined equilibrium concepts,the dynamics converge but are not stable. Some papers in the literatureon implementation with refined equilibrium concepts have claimed that themechanisms they propose are ``simple'' and implement ``everything'' (incontrast with the canonical mechanism). The fact that some of these ``simple''mechanisms have unstable equilibria suggests that these statements shouldbe interpreted with some caution.
Resumo:
Dans cette thèse, nous étudions les aspects comportementaux d'agents qui interagissent dans des systèmes de files d'attente à l'aide de modèles de simulation et de méthodologies expérimentales. Chaque période les clients doivent choisir un prestataire de servivce. L'objectif est d'analyser l'impact des décisions des clients et des prestataires sur la formation des files d'attente. Dans un premier cas nous considérons des clients ayant un certain degré d'aversion au risque. Sur la base de leur perception de l'attente moyenne et de la variabilité de cette attente, ils forment une estimation de la limite supérieure de l'attente chez chacun des prestataires. Chaque période, ils choisissent le prestataire pour lequel cette estimation est la plus basse. Nos résultats indiquent qu'il n'y a pas de relation monotone entre le degré d'aversion au risque et la performance globale. En effet, une population de clients ayant un degré d'aversion au risque intermédiaire encoure généralement une attente moyenne plus élevée qu'une population d'agents indifférents au risque ou très averses au risque. Ensuite, nous incorporons les décisions des prestataires en leur permettant d'ajuster leur capacité de service sur la base de leur perception de la fréquence moyenne d'arrivées. Les résultats montrent que le comportement des clients et les décisions des prestataires présentent une forte "dépendance au sentier". En outre, nous montrons que les décisions des prestataires font converger l'attente moyenne pondérée vers l'attente de référence du marché. Finalement, une expérience de laboratoire dans laquelle des sujets jouent le rôle de prestataire de service nous a permis de conclure que les délais d'installation et de démantèlement de capacité affectent de manière significative la performance et les décisions des sujets. En particulier, les décisions du prestataire, sont influencées par ses commandes en carnet, sa capacité de service actuellement disponible et les décisions d'ajustement de capacité qu'il a prises, mais pas encore implémentées. - Queuing is a fact of life that we witness daily. We all have had the experience of waiting in line for some reason and we also know that it is an annoying situation. As the adage says "time is money"; this is perhaps the best way of stating what queuing problems mean for customers. Human beings are not very tolerant, but they are even less so when having to wait in line for service. Banks, roads, post offices and restaurants are just some examples where people must wait for service. Studies of queuing phenomena have typically addressed the optimisation of performance measures (e.g. average waiting time, queue length and server utilisation rates) and the analysis of equilibrium solutions. The individual behaviour of the agents involved in queueing systems and their decision making process have received little attention. Although this work has been useful to improve the efficiency of many queueing systems, or to design new processes in social and physical systems, it has only provided us with a limited ability to explain the behaviour observed in many real queues. In this dissertation we differ from this traditional research by analysing how the agents involved in the system make decisions instead of focusing on optimising performance measures or analysing an equilibrium solution. This dissertation builds on and extends the framework proposed by van Ackere and Larsen (2004) and van Ackere et al. (2010). We focus on studying behavioural aspects in queueing systems and incorporate this still underdeveloped framework into the operations management field. In the first chapter of this thesis we provide a general introduction to the area, as well as an overview of the results. In Chapters 2 and 3, we use Cellular Automata (CA) to model service systems where captive interacting customers must decide each period which facility to join for service. They base this decision on their expectations of sojourn times. Each period, customers use new information (their most recent experience and that of their best performing neighbour) to form expectations of sojourn time at the different facilities. Customers update their expectations using an adaptive expectations process to combine their memory and their new information. We label "conservative" those customers who give more weight to their memory than to the xiv Summary new information. In contrast, when they give more weight to new information, we call them "reactive". In Chapter 2, we consider customers with different degree of risk-aversion who take into account uncertainty. They choose which facility to join based on an estimated upper-bound of the sojourn time which they compute using their perceptions of the average sojourn time and the level of uncertainty. We assume the same exogenous service capacity for all facilities, which remains constant throughout. We first analyse the collective behaviour generated by the customers' decisions. We show that the system achieves low weighted average sojourn times when the collective behaviour results in neighbourhoods of customers loyal to a facility and the customers are approximately equally split among all facilities. The lowest weighted average sojourn time is achieved when exactly the same number of customers patronises each facility, implying that they do not wish to switch facility. In this case, the system has achieved the Nash equilibrium. We show that there is a non-monotonic relationship between the degree of risk-aversion and system performance. Customers with an intermediate degree of riskaversion typically achieve higher sojourn times; in particular they rarely achieve the Nash equilibrium. Risk-neutral customers have the highest probability of achieving the Nash Equilibrium. Chapter 3 considers a service system similar to the previous one but with risk-neutral customers, and relaxes the assumption of exogenous service rates. In this sense, we model a queueing system with endogenous service rates by enabling managers to adjust the service capacity of the facilities. We assume that managers do so based on their perceptions of the arrival rates and use the same principle of adaptive expectations to model these perceptions. We consider service systems in which the managers' decisions take time to be implemented. Managers are characterised by a profile which is determined by the speed at which they update their perceptions, the speed at which they take decisions, and how coherent they are when accounting for their previous decisions still to be implemented when taking their next decision. We find that the managers' decisions exhibit a strong path-dependence: owing to the initial conditions of the model, the facilities of managers with identical profiles can evolve completely differently. In some cases the system becomes "locked-in" into a monopoly or duopoly situation. The competition between managers causes the weighted average sojourn time of the system to converge to the exogenous benchmark value which they use to estimate their desired capacity. Concerning the managers' profile, we found that the more conservative Summary xv a manager is regarding new information, the larger the market share his facility achieves. Additionally, the faster he takes decisions, the higher the probability that he achieves a monopoly position. In Chapter 4 we consider a one-server queueing system with non-captive customers. We carry out an experiment aimed at analysing the way human subjects, taking on the role of the manager, take decisions in a laboratory regarding the capacity of a service facility. We adapt the model proposed by van Ackere et al (2010). This model relaxes the assumption of a captive market and allows current customers to decide whether or not to use the facility. Additionally the facility also has potential customers who currently do not patronise it, but might consider doing so in the future. We identify three groups of subjects whose decisions cause similar behavioural patterns. These groups are labelled: gradual investors, lumpy investors, and random investor. Using an autocorrelation analysis of the subjects' decisions, we illustrate that these decisions are positively correlated to the decisions taken one period early. Subsequently we formulate a heuristic to model the decision rule considered by subjects in the laboratory. We found that this decision rule fits very well for those subjects who gradually adjust capacity, but it does not capture the behaviour of the subjects of the other two groups. In Chapter 5 we summarise the results and provide suggestions for further work. Our main contribution is the use of simulation and experimental methodologies to explain the collective behaviour generated by customers' and managers' decisions in queueing systems as well as the analysis of the individual behaviour of these agents. In this way, we differ from the typical literature related to queueing systems which focuses on optimising performance measures and the analysis of equilibrium solutions. Our work can be seen as a first step towards understanding the interaction between customer behaviour and the capacity adjustment process in queueing systems. This framework is still in its early stages and accordingly there is a large potential for further work that spans several research topics. Interesting extensions to this work include incorporating other characteristics of queueing systems which affect the customers' experience (e.g. balking, reneging and jockeying); providing customers and managers with additional information to take their decisions (e.g. service price, quality, customers' profile); analysing different decision rules and studying other characteristics which determine the profile of customers and managers.
Resumo:
We consider one-seller assignment markets with multi-unit demands and prove that the associated game is buyers-submodular. Therefore the core is non-empty and it has a lattice structure which contains the allocation where every buyer receives his marginal contribution. We prove that in this kind of market, every pairwise-stable outcome is associated to a competitive equilibrium and viceversa. We study conditions under which the buyers-optimal and the seller-optimal core allocations are competitive equilibrium payoff vectors. Moreover, we characterize the markets for which the core coincidences with the set of competitive equilibria payoff vectors. When agents behave strategically, we introduce a procedure that implements the buyers-optimal core allocation as the unique subgame perfect Nash equilibrium outcome.
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A long-standing question in biology and economics is whether individual organisms evolve to behave as if they were striving to maximize some goal function. We here formalize this "as if" question in a patch-structured population in which individuals obtain material payoffs from (perhaps very complex multimove) social interactions. These material payoffs determine personal fitness and, ultimately, invasion fitness. We ask whether individuals in uninvadable population states will appear to be maximizing conventional goal functions (with population-structure coefficients exogenous to the individual's behavior), when what is really being maximized is invasion fitness at the genetic level. We reach two broad conclusions. First, no simple and general individual-centered goal function emerges from the analysis. This stems from the fact that invasion fitness is a gene-centered multigenerational measure of evolutionary success. Second, when selection is weak, all multigenerational effects of selection can be summarized in a neutral type-distribution quantifying identity-by-descent between individuals within patches. Individuals then behave as if they were striving to maximize a weighted sum of material payoffs (own and others). At an uninvadable state it is as if individuals would freely choose their actions and play a Nash equilibrium of a game with a goal function that combines self-interest (own material payoff), group interest (group material payoff if everyone does the same), and local rivalry (material payoff differences).
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We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.