993 resultados para Games theory


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The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

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The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

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This paper develops an approach to rank testing that nests all existing rank tests andsimplifies their asymptotics. The approach is based on the fact that implicit in every ranktest there are estimators of the null spaces of the matrix in question. The approach yieldsmany new insights about the behavior of rank testing statistics under the null as well as localand global alternatives in both the standard and the cointegration setting. The approach alsosuggests many new rank tests based on alternative estimates of the null spaces as well as thenew fixed-b theory. A brief Monte Carlo study illustrates the results.

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A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

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After years of reciprocal lack of interest, if not opposition, neuroscience and psychoanalysis are poised for a renewed dialogue. This article discusses some aspects of the Freudian metapsychology and its link with specific biological mechanisms. It highlights in particular how the physiological concept of homeostasis resonates with certain fundamental concepts of psychoanalysis. Similarly, the authors underline how the Freud and Damasio theories of brain functioning display remarkable complementarities, especially through their common reference to Meynert and James. Furthermore, the Freudian theory of drives is discussed in the light of current neurobiological evidences of neural plasticity and trace formation and of their relationships with the processes of homeostasis. The ensuing dynamics between traces and homeostasis opens novel avenues to consider inner life in reference to the establishment of fantasies unique to each subject. The lack of determinism, within a context of determinism, implied by plasticity and reconsolidation participates in the emergence of singularity, the creation of uniqueness and the unpredictable future of the subject. There is a gap in determinism inherent to biology itself. Uniqueness and discontinuity: this should today be the focus of the questions raised in neuroscience. Neuroscience needs to establish the new bases of a "discontinuous" biology. Psychoanalysis can offer to neuroscience the possibility to think of discontinuity. Neuroscience and psychoanalysis meet thus in an unexpected way with regard to discontinuity and this is a new point of convergence between them.

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The article is concerned with the formal definition of a largely unnoticed factor in narrative structure. Based on the assumptions that (1) the semantics of a written text depend, among other factors, directly on its visual alignment in space, that (2) the formal structure of a text has to meet that of its spatial presentation and that (3) these assumptions hold true also for narrative texts (which, however, in modern times typically conceal their spatial dimensions by a low-key linear layout), it is argued that, how ever low-key, the expected material shape of a given narrative determines the configuration of its plot by its author. The ,implied book' thus denotes an author's historically assumable, not necessarily conscious idea of how his text, which is still in the process of creation, will be dimensionally presented and under these circumstances visually absorbed. Assuming that an author's knowledge of this later (potentially) substantiated material form influences the composition, the implied book is to be understood as a text-genetically determined, structuring moment of the text. Historically reconstructed, it thus serves the methodical analysis of structural characteristics of a completed text.

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By means of computer simulations and solution of the equations of the mode coupling theory (MCT),we investigate the role of the intramolecular barriers on several dynamic aspects of nonentangled polymers. The investigated dynamic range extends from the caging regime characteristic of glass-formers to the relaxation of the chain Rouse modes. We review our recent work on this question,provide new results, and critically discuss the limitations of the theory. Solutions of the MCT for the structural relaxation reproduce qualitative trends of simulations for weak and moderate barriers. However, a progressive discrepancy is revealed as the limit of stiff chains is approached. This dis-agreement does not seem related with dynamic heterogeneities, which indeed are not enhanced by increasing barrier strength. It is not connected either with the breakdown of the convolution approximation for three-point static correlations, which retains its validity for stiff chains. These findings suggest the need of an improvement of the MCT equations for polymer melts. Concerning the relaxation of the chain degrees of freedom, MCT provides a microscopic basis for time scales from chain reorientation down to the caging regime. It rationalizes, from first principles, the observed deviations from the Rouse model on increasing the barrier strength. These include anomalous scaling of relaxation times, long-time plateaux, and nonmonotonous wavelength dependence of the mode correlators.

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We introduce a model of strategic thinking in games of initial response. Unlike standard level-k models, in this framework the player's `depth of reasoning' is endogenously determined, andit can be disentangled from his beliefs over his opponent's cognitive bound. In our approach,individuals act as if they follow a cost-benefit analysis. The depth of reasoning is a function ofthe player's cognitive abilities and his payoffs. The costs are exogenous and represent the gametheoretical sophistication of the player; the benefit instead is related to the game payoffs. Behavioris in turn determined by the individual's depth of reasoning and his beliefs about the reasoningprocess of the opponent. Thus, in our framework, payoffs not only affect individual choices inthe traditional sense, but they also shape the cognitive process itself. Our model delivers testableimplications on players' chosen actions as incentives and opponents change. We then test themodel's predictions with an experiment. We administer different treatments that vary beliefs overpayoffs and opponents, as well as beliefs over opponents' beliefs. The results of this experiment,which are not accounted for by current models of reasoning in games, strongly support our theory.Our approach therefore serves as a novel, unifying framework of strategic thinking that allows forpredictions across games.

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We present a new phenomenological approach to nucleation, based on the combination of the extended modified liquid drop model and dynamical nucleation theory. The new model proposes a new cluster definition, which properly includes the effect of fluctuations, and it is consistent both thermodynamically and kinetically. The model is able to predict successfully the free energy of formation of the critical nucleus, using only macroscopic thermodynamic properties. It also accounts for the spinodal and provides excellent agreement with the result of recent simulations.

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In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

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We present a model in which particles (or individuals of a biological population) disperse with a rest time between consecutive motions (or migrations) which may take several possible values from a discrete set. Particles (or individuals) may also react (or reproduce). We derive a new equation for the effective rest time T˜ of the random walk. Application to the neolithic transition in Europe makes it possible to derive more realistic theoretical values for its wavefront speed than those following from the single-delayed framework presented previously [J. Fort and V. Méndez, Phys. Rev. Lett. 82, 867 (1999)]. The new results are consistent with the archaeological observations of this important historical process