996 resultados para Nash-bargain


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Optimal tax theory in the Mirrlees’ (1971) tradition implicitly relies on the assumption that all agents are single or that couples may be treated as individuals, despite accumulating evidence against this view of household behavior. We consider an economy where agents may either be single or married, in which case choices result from Nash bargaining between spouses. In such an environment, tax schedules must play the double role of: i) defining households’ objective functions through their impact on threat points, and; ii) inducing the desired allocations as optimal choices for households given these objectives. We find that the taxation principle, which asserts that there is no loss in relying on tax schedules is not valid here: there are constrained efficient allocations which cannot be implemented via taxes. More sophisticated mechanisms expand the set of implementable allocations by: i) aligning the households’ and planner’s objectives; ii) manipulating taxable income elasticities, and; iii) freeing the design of singles’ tax schedules from its consequences on households’ objectives.

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This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables - aerofoil sections - supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality.

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In this paper, the optimal design of an active flow control device; Shock Control Bump (SCB) on suction and pressure sides of transonic aerofoil to reduce transonic total drag is investigated. Two optimisation test cases are conducted using different advanced Evolutionary Algorithms (EAs); the first optimiser is the Hierarchical Asynchronous Parallel Evolutionary Algorithm (HAPMOEA) based on canonical Evolutionary Strategies (ES). The second optimiser is the HAPMOEA is hybridised with one of well-known Game Strategies; Nash-Game. Numerical results show that SCB significantly reduces the drag by 30% when compared to the baseline design. In addition, the use of a Nash-Game strategy as a pre-conditioner of global control saves computational cost up to 90% when compared to the first optimiser HAPMOEA.

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Synopsis and review of the Australian crime film The Square (Nash Edgerton, 2009). Includes cast and credits. The Square is the feature film debut of director Nash Edgerton, well-known in Australian film circles not only for his award-winning music videos and short films Deadline (first prize winner at Tropfest in 1997) and Spider, but also for his work as an actor, editor, producer, writer and stuntman on countless Australian films and television programs. The film was co-written by Edgerton’s regular partner and brother Joel, who also plays the arsonist Billy. Joel is familiar to Australian and international audiences for his television work in The Secret Life of Us as well as numerous film roles...

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Page 57 of the "American Jewish Cavalcade" scrapbook of Leo Baeck in New York found in ROS 10 Folder 3

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Mobile applications are being increasingly deployed on a massive scale in various mobile sensor grid database systems. With limited resources from the mobile devices, how to process the huge number of queries from mobile users with distributed sensor grid databases becomes a critical problem for such mobile systems. While the fundamental semantic cache technique has been investigated for query optimization in sensor grid database systems, the problem is still difficult due to the fact that more realistic multi-dimensional constraints have not been considered in existing methods. To solve the problem, a new semantic cache scheme is presented in this paper for location-dependent data queries in distributed sensor grid database systems. It considers multi-dimensional constraints or factors in a unified cost model architecture, determines the parameters of the cost model in the scheme by using the concept of Nash equilibrium from game theory, and makes semantic cache decisions from the established cost model. The scenarios of three factors of semantic, time and locations are investigated as special cases, which improve existing methods. Experiments are conducted to demonstrate the semantic cache scheme presented in this paper for distributed sensor grid database systems.

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A generalization of Nash-Williams′ lemma is proved for the Structure of m-uniform null (m − k)-designs. It is then applied to various graph reconstruction problems. A short combinatorial proof of the edge reconstructibility of digraphs having regular underlying undirected graphs (e.g., tournaments) is given. A type of Nash-Williams′ lemma is conjectured for the vertex reconstruction problem.

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This paper considers a multi-person discrete game with random payoffs. The distribution of the random payoff is unknown to the players and further none of the players know the strategies or the actual moves of other players. A class of absolutely expedient learning algorithms for the game based on a decentralised team of Learning Automata is presented. These algorithms correspond, in some sense, to rational behaviour on the part of the players. All stable stationary points of the algorithm are shown to be Nash equilibria for the game. It is also shown that under some additional constraints on the game, the team will always converge to a Nash equilibrium.

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Bid optimization is now becoming quite popular in sponsored search auctions on the Web. Given a keyword and the maximum willingness to pay of each advertiser interested in the keyword, the bid optimizer generates a profile of bids for the advertisers with the objective of maximizing customer retention without compromising the revenue of the search engine. In this paper, we present a bid optimization algorithm that is based on a Nash bargaining model where the first player is the search engine and the second player is a virtual agent representing all the bidders. We make the realistic assumption that each bidder specifies a maximum willingness to pay values and a discrete, finite set of bid values. We show that the Nash bargaining solution for this problem always lies on a certain edge of the convex hull such that one end point of the edge is the vector of maximum willingness to pay of all the bidders. We show that the other endpoint of this edge can be computed as a solution of a linear programming problem. We also show how the solution can be transformed to a bid profile of the advertisers.

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Unlike zero-sum stochastic games, a difficult problem in general-sum stochastic games is to obtain verifiable conditions for Nash equilibria. We show in this paper that by splitting an associated non-linear optimization problem into several sub-problems, characterization of Nash equilibria in a general-sum discounted stochastic games is possible. Using the aforementioned sub-problems, we in fact derive a set of necessary and sufficient verifiable conditions (termed KKT-SP conditions) for a strategy-pair to result in Nash equilibrium. Also, we show that any algorithm which tracks the zero of the gradient of the Lagrangian of every sub-problem provides a Nash strategy-pair. (c) 2012 Elsevier Ltd. All rights reserved.

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El presente trabajo se desarrolló en la finca CHELOL, sede del Centro Nacional de Vetiver, propiedad de la Cooperativa Agropecuaria “Ing. Humberto Tapia Barquero”, ubicado en el Municipio de Jinotepe, Carazo, en el período comprendido del 12 de enero al 21 de abril del año 2003. Se evaluó el efecto del tiempo de inmersión en agua en el desarrollo foliar y radical en vástagos de la gramínea vetiver con un testigo. El objetivo es generar información tecnológica que favorezca el prendimiento y desarrollo de vástagos de esta gramínea, para ser establecidos como barrera viva en acciones de conservación de suelo y agua. Se utilizó un diseño completamente aleatorio (DCA) con seis tratamientos de treinta observaciones cada uno. Los resultados mostraron diferencias altamente significativas entre los tratamientos, sobresaliendo, con respecto a velocidad de crecimiento radical y peso del área foliar, velocidad de crecimiento radical y mortalidad de vástagos, eficiencia y beneficios económicos, el tratamiento de inmersión de vástagos de vetiver durante cuarenta y ocho horas. En términos generales, el prendimiento de los vástagos en los tratamientos con inmersión en agua fueron superiores comparado al testigo en el que se aplicó la técnica tradicional.

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Social interactions in classic cognitive games like the ultimatum game or the prisoner's dilemma typically lead to Nash equilibria when multiple competitive decision makers with perfect knowledge select optimal strategies. However, in evolutionary game theory it has been shown that Nash equilibria can also arise as attractors in dynamical systems that can describe, for example, the population dynamics of microorganisms. Similar to such evolutionary dynamics, we find that Nash equilibria arise naturally in motor interactions in which players vie for control and try to minimize effort. When confronted with sensorimotor interaction tasks that correspond to the classical prisoner's dilemma and the rope-pulling game, two-player motor interactions led predominantly to Nash solutions. In contrast, when a single player took both roles, playing the sensorimotor game bimanually, cooperative solutions were found. Our methodology opens up a new avenue for the study of human motor interactions within a game theoretic framework, suggesting that the coupling of motor systems can lead to game theoretic solutions.