Cette thèse étudie des problèmes d’optimisation distribuée avec différentes structures d’observationset leurs applications aux réseaux sans fil et aux problèmes de Smart Grids. Spécifiquement,une structure d’observation asymétrique entre deux agents est considérée, où un premieragent a connaissance complète à propos de la réalisation d’un état aléatoire, et l’autre agent neconnaît rien à propos de cet état. Dans ce contexte, la question est de savoir comment transmettrede l’information depuis le premier agent vers le second agent dans le but d’utiliser de manièreoptimale les ressources de communication. Plusieurs modèles sont étudiés dans cette thèse. Pourtous, un élément commun est le fait que la source d’information doit être encodée de manièreappropriée pour optimiser l’utilisation de la configuration du système. Un premier modèle estétudié où aucun canal de communication n’est disponible entre les agents et ils ont une fonctiond’utilité commune. Cependant, le seul moyen de communiquer est via les actions choisiespar les agents. Comme les actions ont une influence sur le paiement, l’agent informé encode saconnaissance à propos de l’état dans ses actions, qui seront observées de manière imparfaite parle second agent. Ce dernier décodera l’information et choisira ses actions dans le but de maximiserla fonction objectif commune. Nous utilisons des outils de théorie de l’information pourcaractériser ce compromis optimal par une contrainte d’information, et appliquons ce scénario àun problème de contrôle de puissance pour un canal à interférence. Notre nouvelle stratégie (lecontrôle de puissance codé) donne des gains très prometteurs comparés aux approches classiques.Dans une seconde partie, nous considérons qu’il existe un canal dédié de communication, c’està-dire que les actions de l’agent informé n’ont pas d’influence sur le paiement et sont seulementutiles pour la transmission d’information. De plus, les agents sont supposés avoir des intérêtsdivergents, si bien que l’agent informé n’a pas nécessairement d’incitation à envoyer tout sonsavoir à l’agent non informé. La théorie des jeux et les jeux de « Cheap talk » en particulier sontle bon cadre pour analyser ce genre de problème. Nous caractérisons le schéma de signal sur lequelles agents se seront mis d’accord. Ce schéma amènera à un équilibre de Nash, est donc optimiserala façon dont la communication est faite. Ce modèle est d’un intérêt particulier pour les réseauxde véhicules électriques où un véhicule électrique doit envoyer son besoin en terme de puissancede charge à un aggrégateur qui choisira un niveau de charge effectif pour le véhicule électrique.Ce dernier ne se souciera que de son besoin, alors que l’aggrégateur se soucie également de l’étatdu réseau. Ce modèle aide à optimiser la façon dont le réseau est utilisé.Enfin, nous considérons un modèle avec plus de deux agents, où le but principal est pourtous les agents de retrouver l’observation parfaite des actions passées de tous les agents. Ceci estd’un intérêt très particulier d’un point de vue de la théorie des jeux pour caractériser les utilitésespérées de long terme des agents. Dans ce modèle, nous ajoutons un encodeur qui observeparfaitement toutes les actions passées et aidera les agents à obtenir l’observation parfaite. Enfait, ceci sera possible si la bonne contrainte d’information est satisfaite. Nous caractérisonsdonc cette dernière, en utilisant un schéma de codage hybride combinant des outils classiques dethéorie de l’information ainsi que des outils de la théorie des graphes / This thesis studies distributed optimization problems with different observation structuresand application to wireless network and Smart Grids problems. Specifically, an asymmetricobservation structure between two agents is considered, where a first agent has full knowledgeabout the realization of a random state, and the other agent does not know anything about thisstate. In this context, the question is how to transmit information from the first agent to thesecond agent in order to use in an optimal way the communication resources. Several modelsare studied in this thesis. For all of them, a common element is that the information source hasto be encoded in an appropriate manner to optimize the use of the system’s configuration. Afirst model is studied where no dedicated channel for communication is available between agentsand they have the same objective function. Therefore, the only way communication is possible isthrough the actions chosen by agents. As actions are payoff relevant, the first agent has to findthe optimal tradeoff between transmission of information and payoff maximization. The informedagent encodes his knowledge about the state into his actions, which will be imperfectly observedby the second agent. The latter will decode the information and choose his actions in order tomaximize the common objective function. We use tools from information theory to characterizethis optimal tradeoff by an information constraint, and apply this scenario to a power controlproblem in an interference channel setting. Our new strategy (the coded power control ) givessome promising gains compare to classical approaches.In a second part, we consider that there exists a dedicated channel for communication, that isto say the actions of the informed agent are not payoff relevant and are only useful for transmissionof information. Furthermore, agents are supposed to have diverging interests, so that the informedagent does not necessarily have an incentive to send all his knowledge to the uninformed agent.Game theory and Cheap talk game in particular appears to be the right framework to analyzethis problem. We characterize the signal scheme that agents will agree on. This scheme willlead to a Nash Equilibrium, thus will optimize the way communication is done. This model is ofparticular interest for electrical vehicles networks where an electrical vehicle has to send his needin term of power to an aggregator which will choose an effective charging level for the electricalvehicle. The latter only cares about his need in term of power whereas the aggregator also takesinto account the network status. The considered model help to optimize the way the network isused.We finally consider a model with more than two agents, where the main goal is for all agentsto retrieve perfect observations of all past actions of all agents. This is of particular interest ina game theory point of view to characterize the long term expected utilities of the agents. Inthis model, we add an encoder who perfectly oberves all past actions and will help agents tohave perfect monitoring. In fact, this is possible if the right information constraint is satisfied.We thus characterized the latter, using a hybrid coding scheme combining classical informationtheoretic scheme and tools from graph theory.

Submitted by Vivian Malta Nunes (vivianmalta@yahoo.com.br) on 2013-12-18T16:26:21Z No. of bitstreams: 1 Tese_Vivian_Final.pdf: 1556413 bytes, checksum: d21c4cfb4b686d356131b508247b2cc4 (MD5) / Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2014-01-28T17:57:42Z (GMT) No. of bitstreams: 1 Tese_Vivian_Final.pdf: 1556413 bytes, checksum: d21c4cfb4b686d356131b508247b2cc4 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2014-02-03T16:12:27Z (GMT) No. of bitstreams: 1 Tese_Vivian_Final.pdf: 1556413 bytes, checksum: d21c4cfb4b686d356131b508247b2cc4 (MD5) / Made available in DSpace on 2014-02-03T16:12:45Z (GMT). No. of bitstreams: 1 Tese_Vivian_Final.pdf: 1556413 bytes, checksum: d21c4cfb4b686d356131b508247b2cc4 (MD5) Previous issue date: 2013-06-18 / This thesis studies price-setting models and analyzes their macroeconomic im- plications. In the rst two chapters I study general models in which rms pricing decisions are a¤ected by menu costs and information costs. In Chapter 1 I estimate these models using American data on price changes, concluding that: information costs are signi cantly higher than menu costs; real data does not t into the model in which rms receive information about aggregate conditions freely but pay for idio- syncratic information. In Chapter 2 I explore the consequences of monetary shocks and disin ation announcements using the previously estimated models. I show that the degree of monetary non-neutrality is larger in an economy where part of the infor- mation is given for free. Chapter 3 is a coauthored paper with Carlos Carvalho and Antonella Tutino. We abstract from menu costs and examine a price-setting model in which rms are subject to a Shannon constraint on information ow. We calibrate the model and investigate impulse response functions to aggregate and idiosyncratic shocks. We nd that, rather than tracking aggregate and idiosyncratic conditions independently, rms prefer to process information altogether, and that leads to a faster overall price level adjustment, and thus to less real e¤ects persistence after a monetary shock. / Esta tese se dedica ao estudo de modelos de fixação de preços e suas implicações macroeconômicas. Nos primeiros dois capítulos analiso modelos em que as decisões das firmas sobre seus preços praticados levam em conta custos de menu e de informação. No Capítulo 1 eu estimo tais modelos empregando estatísticas de variações de preços dos Estados Unidos, e concluo que: os custos de informação são significativamente maiores que os custos de menu; os dados claramente favorecem o modelo em que informações sobre condições agregadas são custosas enquanto que as idiossincráticas têm custo zero. No Capítulo 2 investigo as consequências de choques monetários e anúncios de desinflação usando os modelos previamente estimados. Mostro que o grau de não-neutralidade monetária é maior no modelo em que parte da informação é grátis. O Capítulo 3 é um artigo em conjunto com Carlos Carvalho (PUC-Rio) e Antonella Tutino (Federal Reserve Bank of Dallas). No artigo examinamos um modelo de fixação de preços em que firmas estão sujeitas a uma restrição de fluxo de informação do tipo Shannon. Calibramos o modelo e estudamos funções impulso-resposta a choques idiossincráticos e agregados. Mostramos que as firmas vão preferir processar informações agregadas e idiossincráticas conjuntamente ao invés de investigá-las separadamente. Este tipo de processamento gera ajustes de preços mais frequentes, diminuindo a persistência de efeitos reais causados por choques monetários.