979 resultados para Théorie de jeux


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Il a été démontré en laboratoire que l’équilibre de Nash n’était pas toujours un bon indicateur du comportement humain. Différentes théories alternatives (aversion à l’inégalité, réciprocité et norme sociale) ont vu le jour pour combler les lacunes de la théorie classique, mais aucune d’elles ne permet d’expliquer la totalité des phénomènes observés en laboratoire. Après avoir identifié les lacunes de ces modèles, ce mémoire développe un modèle qui synthétise dans un tout cohérent les avancées de ceux-ci à l’aide de préférences hétérogènes. Afin d’augmenter la portée du modèle, une nouvelle notion d’équilibre, dite comportementale, est ajoutée au modèle. En appliquant le nouveau modèle à des jeux simples, nous pouvons voir comment il élargit le nombre de comportements pouvant être modélisé par la théorie des jeux.

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How do sportspeople succeed in a non-collaborative game? An illustration of a perverse side effect of altruism Are team sports specialists predisposed to collaboration? The scientific literature on this topic is divided. The present article attempts to end this debate by applying experimental game theory. We constituted three groups of volunteers (all students aged around 20): 25 team sports specialists; 23 individual sports specialists (gymnasts, track & field athletes and swimmers) and a control group of 24 non-sportspeople. Each subgroup was divided into 3 teams that played against each other in turn (and not against teams from other subgroups). The teams played a game based on the well-known Prisoner's Dilemma (Tucker, 1950) - the paradoxical "Bluegill Sunbass Game" (Binmore, 1999) with three Nash equilibria (two suboptimal equilibria with a pure strategy and an optimal equilibrium with a mixed, egotistical strategy (p= 1/2)). This game also features a Harsanyi equilibrium (based on constant compliance with a moral code and altruism by empathy: "do not unto others that which you would not have them do unto you"). How, then, was the game played? Two teams of 8 competed on a handball court. Each team wore a distinctive jersey. The game lasted 15 minutes and the players were allowed to touch the handball ball with their feet or hands. After each goal, each team had to return to its own half of the court. Players were allowed to score in either goal and thus cooperate with their teammates or not, as they saw fit. A goal against the nominally opposing team (a "guardian" strategy, by analogy with the Bluegill Sunbass Game) earned a point for everyone in the team. For an own goal (a "sneaker" strategy), only the scorer earned a point - hence the paradox. If all the members of a team work together to score a goal, everyone is happy (the Harsanyi solution). However, the situation was not balanced in the Nashian sense: each player had a reason to be disloyal to his/her team at the merest opportunity. But if everyone adopts a "sneaker" strategy, the game becomes a free-for-all and the chances of scoring become much slimmer. In a context in which doubt reigns as to the honesty of team members and "legal betrayals", what type of sportsperson will score the most goals? By analogy with the Bluegill Sunbass Game, we recorded direct motor interactions (passes and shots) based on either a "guardian" tactic (i.e. collaboration within the team) or a "sneaker" tactic (shots and passes against the player's designated team). So, was the group of team sports specialist more collaborative than the other two groups? The answer was no. A statistical analysis (difference from chance in a logistic regression) enabled us to draw three conclusions: ?For the team sports specialists, the Nash equilibrium (1950) was stronger than the Harsanyi equilibrium (1977). ?The sporting principles of equilibrium and exclusivity are not appropriate in the Bluegill Sunbass Game and are quickly abandoned by the team sports specialists. The latter are opportunists who focus solely on winning and do well out of it. ?The most altruistic players are the main losers in the Bluegill Sunbass Game: they keep the game alive but contribute to their own defeat. In our experiment, the most altruistic players tended to be the females and the individual sports specialists

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How do sportspeople succeed in a non-collaborative game? An illustration of a perverse side effect of altruism Are team sports specialists predisposed to collaboration? The scientific literature on this topic is divided. The present article attempts to end this debate by applying experimental game theory. We constituted three groups of volunteers (all students aged around 20): 25 team sports specialists; 23 individual sports specialists (gymnasts, track & field athletes and swimmers) and a control group of 24 non-sportspeople. Each subgroup was divided into 3 teams that played against each other in turn (and not against teams from other subgroups). The teams played a game based on the well-known Prisoner's Dilemma (Tucker, 1950) - the paradoxical "Bluegill Sunbass Game" (Binmore, 1999) with three Nash equilibria (two suboptimal equilibria with a pure strategy and an optimal equilibrium with a mixed, egotistical strategy (p= 1/2)). This game also features a Harsanyi equilibrium (based on constant compliance with a moral code and altruism by empathy: "do not unto others that which you would not have them do unto you"). How, then, was the game played? Two teams of 8 competed on a handball court. Each team wore a distinctive jersey. The game lasted 15 minutes and the players were allowed to touch the handball ball with their feet or hands. After each goal, each team had to return to its own half of the court. Players were allowed to score in either goal and thus cooperate with their teammates or not, as they saw fit. A goal against the nominally opposing team (a "guardian" strategy, by analogy with the Bluegill Sunbass Game) earned a point for everyone in the team. For an own goal (a "sneaker" strategy), only the scorer earned a point - hence the paradox. If all the members of a team work together to score a goal, everyone is happy (the Harsanyi solution). However, the situation was not balanced in the Nashian sense: each player had a reason to be disloyal to his/her team at the merest opportunity. But if everyone adopts a "sneaker" strategy, the game becomes a free-for-all and the chances of scoring become much slimmer. In a context in which doubt reigns as to the honesty of team members and "legal betrayals", what type of sportsperson will score the most goals? By analogy with the Bluegill Sunbass Game, we recorded direct motor interactions (passes and shots) based on either a "guardian" tactic (i.e. collaboration within the team) or a "sneaker" tactic (shots and passes against the player's designated team). So, was the group of team sports specialist more collaborative than the other two groups? The answer was no. A statistical analysis (difference from chance in a logistic regression) enabled us to draw three conclusions: ?For the team sports specialists, the Nash equilibrium (1950) was stronger than the Harsanyi equilibrium (1977). ?The sporting principles of equilibrium and exclusivity are not appropriate in the Bluegill Sunbass Game and are quickly abandoned by the team sports specialists. The latter are opportunists who focus solely on winning and do well out of it. ?The most altruistic players are the main losers in the Bluegill Sunbass Game: they keep the game alive but contribute to their own defeat. In our experiment, the most altruistic players tended to be the females and the individual sports specialists

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How do sportspeople succeed in a non-collaborative game? An illustration of a perverse side effect of altruism Are team sports specialists predisposed to collaboration? The scientific literature on this topic is divided. The present article attempts to end this debate by applying experimental game theory. We constituted three groups of volunteers (all students aged around 20): 25 team sports specialists; 23 individual sports specialists (gymnasts, track & field athletes and swimmers) and a control group of 24 non-sportspeople. Each subgroup was divided into 3 teams that played against each other in turn (and not against teams from other subgroups). The teams played a game based on the well-known Prisoner's Dilemma (Tucker, 1950) - the paradoxical "Bluegill Sunbass Game" (Binmore, 1999) with three Nash equilibria (two suboptimal equilibria with a pure strategy and an optimal equilibrium with a mixed, egotistical strategy (p= 1/2)). This game also features a Harsanyi equilibrium (based on constant compliance with a moral code and altruism by empathy: "do not unto others that which you would not have them do unto you"). How, then, was the game played? Two teams of 8 competed on a handball court. Each team wore a distinctive jersey. The game lasted 15 minutes and the players were allowed to touch the handball ball with their feet or hands. After each goal, each team had to return to its own half of the court. Players were allowed to score in either goal and thus cooperate with their teammates or not, as they saw fit. A goal against the nominally opposing team (a "guardian" strategy, by analogy with the Bluegill Sunbass Game) earned a point for everyone in the team. For an own goal (a "sneaker" strategy), only the scorer earned a point - hence the paradox. If all the members of a team work together to score a goal, everyone is happy (the Harsanyi solution). However, the situation was not balanced in the Nashian sense: each player had a reason to be disloyal to his/her team at the merest opportunity. But if everyone adopts a "sneaker" strategy, the game becomes a free-for-all and the chances of scoring become much slimmer. In a context in which doubt reigns as to the honesty of team members and "legal betrayals", what type of sportsperson will score the most goals? By analogy with the Bluegill Sunbass Game, we recorded direct motor interactions (passes and shots) based on either a "guardian" tactic (i.e. collaboration within the team) or a "sneaker" tactic (shots and passes against the player's designated team). So, was the group of team sports specialist more collaborative than the other two groups? The answer was no. A statistical analysis (difference from chance in a logistic regression) enabled us to draw three conclusions: ?For the team sports specialists, the Nash equilibrium (1950) was stronger than the Harsanyi equilibrium (1977). ?The sporting principles of equilibrium and exclusivity are not appropriate in the Bluegill Sunbass Game and are quickly abandoned by the team sports specialists. The latter are opportunists who focus solely on winning and do well out of it. ?The most altruistic players are the main losers in the Bluegill Sunbass Game: they keep the game alive but contribute to their own defeat. In our experiment, the most altruistic players tended to be the females and the individual sports specialists

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It is well-known that non-cooperative and cooperative game theory may yield different solutions to games. These differences are particularly dramatic in the case of truels, or three-person duels, in which the players may fire sequentially or simultaneously, and the games may be one-round or n-round. Thus, it is never a Nash equilibrium for all players to hold their fire in any of these games, whereas in simultaneous one-round and n-round truels such cooperation, wherein everybody survives, is in both the a -core and ß -core. On the other hand, both cores may be empty, indicating a lack of stability, when the unique Nash equilibrium is one survivor. Conditions under which each approach seems most applicable are discussed. Although it might be desirable to subsume the two approaches within a unified framework, such unification seems unlikely since the two approaches are grounded in fundamentally different notions of stability.

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This paper develops and estimates a game-theoretical model of inflation targeting where the central banker's preferences are asymmetric around the targeted rate. In particular, positive deviations from the target can be weighted more, or less, severely than negative ones in the central banker's loss function. It is shown that some of the previous results derived under the assumption of symmetry are not robust to the generalization of preferences. Estimates of the central banker's preference parameters for Canada, Sweden, and the United Kingdom are statistically different from the ones implied by the commonly used quadratic loss function. Econometric results are robust to different forecasting models for the rate of unemployment but not to the use of measures of inflation broader than the one targeted.

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The rationalizability of a choice function by means of a transitive relation has been analyzed thoroughly in the literature. However, not much seems to be known when transitivity is weakened to quasi-transitivity or acyclicity. We describe the logical relationships between the different notions of rationalizability involving, for example, the transitivity, quasi-transitivity, or acyclicity of the rationalizing relation. Furthermore, we discuss sufficient conditions and necessary conditions for rational choice on arbitrary domains. Transitive, quasi-transitive, and acyclical rationalizability are fully characterized for domains that contain all singletons and all two-element subsets of the universal set.

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A contingent contract in a transferable utility game under uncertainty specifies an outcome for each possible state. It is assumed that coalitions evaluate these contracts by considering the minimal possible excesses. A main question of the paper concerns the existence and characterization of efficient contracts. It is shown that they exist if and only if the set of possible coalitions contains a balanced subset. Moreover, a characterization of values that result in efficient contracts in the case of minimally balanced collections is provided.

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We propose two axiomatic theories of cost sharing with the common premise that agents demand comparable -though perhaps different- commodities and are responsible for their own demand. Under partial responsibility the agents are not responsible for the asymmetries of the cost function: two agents consuming the same amount of output always pay the same price; this holds true under full responsibility only if the cost function is symmetric in all individual demands. If the cost function is additively separable, each agent pays her stand alone cost under full responsibility; this holds true under partial responsibility only if, in addition, the cost function is symmetric. By generalizing Moulin and Shenker’s (1999) Distributivity axiom to cost-sharing methods for heterogeneous goods, we identify in each of our two theories a different serial method. The subsidy-free serial method (Moulin, 1995) is essentially the only distributive method meeting Ranking and Dummy. The cross-subsidizing serial method (Sprumont, 1998) is the only distributive method satisfying Separability and Strong Ranking. Finally, we propose an alternative characterization of the latter method based on a strengthening of Distributivity.

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We consider entry-level medical markets for physicians in the United Kingdom. These markets experienced failures which led to the adoption of centralized market mechanisms in the 1960's. However, different regions introduced different centralized mechanisms. We advise physicians who do not have detailed information about the rank-order lists submitted by the other participants. We demonstrate that in each of these markets in a low information environment it is not beneficial to reverse the true ranking of any two acceptable hospital positions. We further show that (i) in the Edinburgh 1967 market, ranking unacceptable matches as acceptable is not profitable for any participant and (ii) in any other British entry-level medical market, it is possible that only strategies which rank unacceptable positions as acceptable are optimal for a physician.

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We reconsider the following cost-sharing problem: agent i = 1,...,n demands a quantity xi of good i; the corresponding total cost C(x1,...,xn) must be shared among the n agents. The Aumann-Shapley prices (p1,...,pn) are given by the Shapley value of the game where each unit of each good is regarded as a distinct player. The Aumann-Shapley cost-sharing method assigns the cost share pixi to agent i. When goods come in indivisible units, we show that this method is characterized by the two standard axioms of Additivity and Dummy, and the property of No Merging or Splitting: agents never find it profitable to split or merge their demands.

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We introduce a procedure to infer the repeated-game strategies that generate actions in experimental choice data. We apply the technique to set of experiments where human subjects play a repeated Prisoner's Dilemma. The technique suggests that two types of strategies underly the data.

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A group of agents participate in a cooperative enterprise producing a single good. Each participant contributes a particular type of input; output is nondecreasing in these contributions. How should it be shared? We analyze the implications of the axiom of Group Monotonicity: if a group of agents simultaneously decrease their input contributions, not all of them should receive a higher share of output. We show that in combination with other more familiar axioms, this condition pins down a very small class of methods, which we dub nearly serial.

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The following properties of the core of a one well-known: (i) the core is non-empty; (ii) the core is a lattice; and (iii) the set of unmatched agents is identical for any two matchings belonging to the core. The literature on two-sided matching focuses almost exclusively on the core and studies extensively its properties. Our main result is the following characterization of (von Neumann-Morgenstern) stable sets in one-to-one matching problem only if it is a maximal set satisfying the following properties : (a) the core is a subset of the set; (b) the set is a lattice; (c) the set of unmatched agents is identical for any two matchings belonging to the set. Furthermore, a set is a stable set if it is the unique maximal set satisfying properties (a), (b) and (c). We also show that our main result does not extend from one-to-one matching problems to many-to-one matching problems.