It is known that quantum strategies change the range of possible payoffs for the players in the prisoner's dilemma. In this paper, we examine the effect of the degree of entanglement in determining the payoffs. When both players play quantum strategies, we show that the payoff for both players is unaffected by the entanglement value and it leads to a new Nash equilibrium.

Nous appliquons la théorie asymptotique des expériences statistiques à des problèmes liés aux valeurs extrêmes. Quatre modèles semi-paramétriques sont envisagés. Tout d'abord le modèle d'échantillonnage de fonction de répartition de type Pareto. L'index de Pareto est le paramètre d'intérêt tandis que la fonction à variation lente, qui intervient dans la décomposition de la fonction de survie, joue le rôle de nuisance. Nous considérons ensuite des observations i.i.d. de fonction de répartition de type Weibull. Le troisième modèle étudié est un modèle de régression. On considère des couples d'observations $(Y_i,X_i)$ indépendants, les v.a. $X_i$ sont i.i.d. de loi connue et on suppose que la fonction de répartition de la loi de $Y$ conditionnellement à $X$ est de type Pareto, avec une fonction à variation lente et un index $gamma$ qui dépendent de $X$. On fait l'hypothèse que la fonction $gamma$ a une forme quelconque mais connue, qui dépend d'un paramètre $ heta$ dans $SR^K$. Le paramètre d'intérêt est $ heta$. Enfin, nous étudions un modèle linéaire avec des innovations de fonction de répartition de type Pareto. Pour chacun de ces modèles, notre démarche est de construire des alternatives, d'établir la normalité locale asymptotique et l'existence d'un estimateur asymptotiquement efficace, ce qui n'est possible que parce que les alternatives que nous avons construites sont des alternatives les plus difficiles. Pour les deux derniers modèles, l'estimateur asymptotiquement efficace que nous proposons n'a, à notre connaissance, pas encore fait l'objet d'une publication.

Hydraulic tomography (HT) has become a mature aquifer test technology over the last two decades. It collects nonredundant information of aquifer heterogeneity by sequentially stressing the aquifer at different wells and collecting aquifer responses at other wells during each stress. The collected information is then interpreted by inverse models. Among these models, the geostatistical approaches, built upon the Bayesian framework, first conceptualize hydraulic properties to be estimated as random fields, which are characterized by means and covariance functions. They then use the spatial statistics as prior information with the aquifer response data to estimate the spatial distribution of the hydraulic properties at a site. Since the spatial statistics describe the generic spatial structures of the geologic media at the site rather than site-specific ones (e. g., known spatial distributions of facies, faults, or paleochannels), the estimates are often not optimal. To improve the estimates, we introduce a general statistical framework, which allows the inclusion of site-specific spatial patterns of geologic features. Subsequently, we test this approach with synthetic numerical experiments. Results show that this approach, using conditional mean and covariance that reflect site-specific large-scale geologic features, indeed improves the HT estimates. Afterward, this approach is applied to HT surveys at a kilometerscale- fractured granite field site with a distinct fault zone. We find that by including fault information from outcrops and boreholes for HT analysis, the estimated hydraulic properties are improved. The improved estimates subsequently lead to better prediction of flow during a different pumping test at the site.

L'intégration tridimensionnelle (3D), où plusieurs puces sont empilées et interconnectées, est en train de révolutionner l'industrie des semi-conducteurs.Cette technologie permet d'associer, dans un même boîtier, des puces électroniques (analogique, numérique, mémoire) avec des puces d'autres domaines(MEMS, bio-capteurs, optique, etc). Cela ouvre de nombreuses voies d'innovation. Néanmoins, l'absence d'outils de conception assistée ordinateur(CAO) adaptés aux systèmes 3D freine l'adoption de la technologie.Cette thèse contribue à deux problématiques liées à la conception 3D : le partitionnement d'un système sur de multiples puces et l'optimisation hiérarchique de systèmes multiphysiques (hétérogènes).La première partie de la thèse est dédiée au problème de partitionner la fonctionnalité d'un système sur de multiples puces. Un outil de « floorplan » 3D a été développé pour optimiser ce partitionnement en fonction de la surface des puces, de la température d'opération du circuit et de la structure des interconnexions. Ce type d'outil étant complexe, nous proposons de régler ses paramètres de façon automatique par l'utilisation d'algorithmes évolutionnaires.Des résultats expérimentaux sur une suite de benchmarks et sur une architecture multi processeur connecté en réseau démontrent l'efficacité et l'applicabilité des techniques d'optimisation proposées.Dans la deuxième partie, nous présentons une méthodologie de conception hiérarchique qui est adaptée aux systèmes hétérogènes. La méthode combine une approche ascendante et descendante et utilise des courbes de compromis(Fronts de Pareto) comme une abstraction de la performance d'un circuit.La contribution principale de la thèse consiste à utiliser des techniques d'interpolation pour représenter les Fronts de Pareto par des fonctions continues et à leur intégration dans des processus d'optimisation classiques. Cela permet un gain en flexibilité lors de l'étape ascendante du flot (caractérisation) et un gain en temps lors de l'étape descendante (synthèse). Le flot de conception est démontré sur un amplificateur opérationnel ainsi comme sur la synthèse d'un lien optoélectronique avec trois niveaux hiérarchiques. / 3D integration technology is driving a strong paradigm shift in the design of electronic systems. The ability to tightly integrate functions from different technology nodes (analog, digital, memory) and physical domains (MEMS, optics, etc) offers great opportunities for innovation (More than Moore). However, leveraging this potential requires efficient CAD tools to compare architectural choices at early design stages and to co-optimize multiphysics systems.This thesis work is divided into two parts. The first part is dedicated to the problem of partitioning a system into multiple dies. A 3D floorplanning tool was developed to optimize area, temperature and the interconnect structure of a 3DIC. Moreover, a meta-optimization approach based on genetic algorithms is proposed to automatically configure the key parameters of the floorplanner. Tests were carried out on architectural benchmarks and a NoC based multiprocessor to demonstrate the efficiency of the proposed techniques.In the second part of the thesis, a hierarchical design methodology adapted to heterogeneous systems is presented. The method combines the bottom-up and top-down approaches with Pareto-front techniques and response surface modeling. The Pareto front of lower level blocks are extracted and converted into predictive performance models that can be stored and reused in a top-down optimization process. The design flow is demonstrated on an operational amplifier as well as on the synthesis of an optoelectronic data link with three abstraction levels.

In this thesis the problem of conceptual engineering design and the possible use of adaptive search techniques and other machine based methods therein are explored. For the multi-objective optimisation (MOO) within conceptual design problem, genetic algorithms (GA) adapted to MOO are used and various techniques explored: weighted sums, lexicographic order, Pareto method with and without ranking, VEGA-like approaches etc. Large number of runs are performed for findingZ Dth e optimal configuration and setting of the GA parameters. A novel method, weighted Pareto method is introduced and applied to a real-world optimisation problem. Decision support methods within conceptual engineering design framework are discussed and a new preference method developed. The preference method for translating vague qualitative categories (such as "more important 91 , 4m.9u ch less important' 'etc. ) into quantitative values (numbers) is based on fuzzy preferences and graph theory methods. Several applications of preferences are presented and discussed: * in weighted sum based optimisation methods; s in weighted Pareto method; * for ordering and manipulating constraints and scenarios; e for a co-evolutionary, distributive GA-based MOO method; The issue of complexity and sensitivity is addressed as well as potential generalisations of presented preference methods. Interactive dynamical constraints in the form of design scenarios are introduced. These are based on a propositional logic and a fairly rich mathematical language. They can be added, deleted and modified on-line during the design session without need for recompiling the code. The use of machine-based agents in conceptual design process is investigated. They are classified into several different categories (e. g. interface agents, search agents, information agents). Several different categories of agents performing various specialised task are developed (mostly dealing with preferences, but also some filtering ones). They are integrated with the conceptual engineering design system to form a closed loop system that includes both computer and designer. All thesed ifferent aspectso f conceptuale ngineeringd esigna re applied within Plymouth Engineering Design Centre / British Aerospace conceptual airframe design project.

Cette thèse est consacrée à l'étude de l’optimisation combinatoire multi-objective sous incertitudes. Plus particulièrement, nous abordons les problèmes multi-objectifs contenant des données floues qui sont exprimées par des nombres triangulaires floues. Pour faire face à ce type de problèmes, notre idée principale est d’étendre les concepts multi-objectifs classiques au contexte flou. Nous proposons, dans un premier temps, une nouvelle approche Pareto entre des objectifs flous (i.e. vecteurs des nombres triangulaires flous). Ensuite, nous étendons des méta-heuristiques basées sur Pareto afin de converger vers des solutions optimales floues. L’approche proposée est illustrée sur un problème bi-objectif de routage de véhicules avec des demandes floues. Dans le deuxième volet de ce travail, nous abordons l’aspect de robustesse dans le contexte multi-objectif flou en proposant une nouvelle méthodologie d’évaluation de robustesse des solutions. Finalement, les résultats expérimentaux sur des benchmarks flous du problème de routage de véhicules prouvent l’efficacité et la fiabilité de notre approche. / This thesis is devoted to the study of multi-objective combinatorial optimization under uncertainty. In particular, we address multi-objective problems with fuzzy data, in which fuzziness is expressed by fuzzy triangular numbers. To handle such problems, our main idea is to extend the classical multi-objective concepts to fuzzy context. To handle such problems, we proposed a new Pareto approach between fuzzy-valued objectives (i.e. vectors of triangular fuzzy numbers). Then, an extension of Pareto-based metaheuristics is suggested as resolution methods. The proposed approach is thereafter illustrated on a bi-objective vehicle routing problem with fuzzy demands. At the second stage, we address robustness aspect in the multi-objective fuzzy context by proposing a new methodology of robustness evaluation of solutions. Finally, the experimental results on fuzzy benchmarks of vehicle routing problem prove the effectiveness and reliability of our approach.

The aim of this thesis is to conduct a case study examining the intrusion of marketplace ideals on various aspects of everyday life. In this thesis, I provide a case study of a new business in San Francisco, ReservationHop, that transforms the previously first come, first serve restaurant reservation service into an auction style scalping (resell at a higher price) system, thereby affecting the distribution of an economic service, or good. In order to investigate this phenomenon, this thesis is organized into six main sections. First, I will provide a brief introduction to the thesis, presenting my aim and purpose in writing and why I believe that this is an important topic. I then introduce ReservationHop and describe the site and its business model, the controversy that it has evoked, and the app's creator Brian Mayer's attempts to defend the app's legitimacy. Thirdly, I will provide considerations in support of the ethical permissibility of the ReservationHop business model, using two neoclassical economic arguments: consumer choice theory and the Pareto-efficiency argument. Fourthly, I will counter these arguments, claiming that this service is not a Pareto optimal improvement because it involves deception, which is incompatible with genuine Pareto optimality. In the fifth section, I will introduce my main argument against ReservationHop in which I introduce the idea that there is something inherently wrong with the service even if its deceptive characteristics were corrected for. I argue that there should be "things that money cannot buy" because unfettered marketization erodes the nonmarket value of community, or commonality. In conclusion, this thesis argues that the intrusion of marketplace values on all aspects of society should be resisted, and that we must rethink the increased influence of marketization for it crowds out other important non-market values, e.g., our sense of community solidarity.

Master-Arbeit Univ. St. Gallen, 2007.

Thesis--Tübingen. / Cover title. Vita. Includes bibliographical references (p. 79).

Σε αυτήν την εργασία, παρουσιάζουμε τις βασικότερες κλασικές προσεγγίσεις επίλυσης Πολυ-αντικειμενικών Προβλημάτων Βελτιστοποίησης(ΠΠΒ)καθώς και ένα από τα πιο δημοφιλή λογισμικά για επίλυση ΠΠΒ, το NIMBUS. Συγκεκριμένα, δίνουμε τον ορισμό ενός ΠΠΒ, το θεωρητικό υπόβαθρο -- για την καλύτερη κατανόηση των μεθόδων που θα ακολουθήσουν - και τις διαφορές των ΠΠΒ με τα κλασσικά Μονο-αντικειμενικά προβλήματα Βελτιστοποίησης. Επιπλέον, παρουσιάζουμε τις τρεις κύριες κατηγορίες προσέγγισης των ΠΠΒ (μη-αλληλεπιδραστικές, αλληλεπιδραστικές, εξελικτικές) ο διαχωρισμός των οποίων γίνεται ανάλογα με την άμεση ή έμμεση εμπλοκή του Λήπτη Απόφασης. Η μελέτη μας εστιάζεται κυρίως στην κατηγορία των μη-αλληλεπιδραστικών προσεγγίσεων, στην οποία ο ΛΑ εμπλέκεται έμμεσα. Τέλος, ολοκληρώνουμε την μελέτη μας με την αναλυτική παρουσίαση της επίλυσης ενός ΠΠB με την χρήση του λογισμικού NIMBUS. / In this contribution, we study the classical approaches for solving Multi-objective Optimization Problems (MOOP) as well as one of the most popular software that solves MOOP, namely NIMBUS. More specifically, we present the definition and the theoretical background around MOOP and we discuss the differences between MOOP and the classical single-objective optimization problems. We also present the three main categories of approaches of solving MOOP (non-interactive, interactive, evolutionary) that are characterized by the way the Decision Maker participates in the solution. We focus on the first category by analyzing each of the non-interactive approaches. Finally, we conclude by presenting an analytic illustration of an example that solves a MOOP using the NIMBUS software.