985 resultados para Incomplete information


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The notion of common prior is well-understood and widely-used in the incomplete information games literature. For ordinary type spaces the common prior is defined. Pinter and Udvari (2011) introduce the notion of generalized type space. Generalized type spaces are models for various bonded rationality issues, for nite belief hierarchies, unawareness among others. In this paper we dene the notion of common prior for generalized types spaces. Our results are as follows: the generalization (1) suggests a new form of common prior for ordinary type spaces, (2) shows some quantum game theoretic results (Brandenburger and La Mura, 2011) in new light.

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Over the past decade, Mental Health (MH) has increasingly appeared on the ‘school agenda’, both in terms of rising levels of MH difficulties in the student population, and also the expectation that schools have a role to play in supporting good MH. MH is a term fraught with ambiguities leading to uncertainty around the most appropriate ways to provide support. A review of current literature reveals a wide range of definitions and interpretations, sometimes within the same team of supporting professionals. The current study seeks to explore the perspectives held by two professional groups seemingly well placed to support young persons’ (YPs’) MH. Six Clinical Psychologists (CPs) and six Educational Psychologists (EPs) are interviewed, exploring their constructs of MH, and their perceptions of their own role and the roles of others in supporting secondary school aged YPs’ MH. The data are analysed through Thematic Analysis. Findings suggest that there are variations between the two professions’ constructs of MH, and EPs in particular have no unified concept of MH. This is likely due to less experience or training in this area. CPs and EPs hold similar perceptions of the school’s role for promoting good MH, and flagging up concerns to more specialist professionals when necessary. However, there are discrepancies in the EP and CP perceptions of each other’s roles. The conflicting views appear to emerge through incomplete information about the other, and professional defensiveness in a context where resources and funding are scarce. The current study suggests that these challenges can be addressed through: greater reflectivity on professional biases, exploration of MH constructs within other epistemological positions, and greater communication regarding professional roles, leading to clearer collaboration in supporting the MH of YP.

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Interações sociais são frequentemente descritas como trocas sociais. Na literatura, trocas sociais em Sistemas Multiagentes são objeto de estudo em diversos contextos, nos quais as relações sociais são interpretadas como trocas sociais. Dentre os problemas estudados, um problema fundamental discutido na literatura e a regulação¸ ao de trocas sociais, por exemplo, a emergência de trocas equilibradas ao longo do tempo levando ao equilíbrio social e/ou comportamento de equilíbrio/justiça. Em particular, o problema da regulação de trocas sociais e difícil quando os agentes tem informação incompleta sobre as estratégias de troca dos outros agentes, especificamente se os agentes tem diferentes estratégias de troca. Esta dissertação de mestrado propõe uma abordagem para a autorregulacao de trocas sociais em sistemas multiagentes, baseada na Teoria dos Jogos. Propõe o modelo de Jogo de Autorregulacão ao de Processos de Trocas Sociais (JAPTS), em uma versão evolutiva e espacial, onde os agentes organizados em uma rede complexa, podem evoluir suas diferentes estratégias de troca social. As estratégias de troca são definidas através dos parâmetros de uma função de fitness. Analisa-se a possibilidade do surgimento do comportamento de equilíbrio quando os agentes, tentando maximizar sua adaptação através da função de fitness, procuram aumentar o numero de interações bem sucedidas. Considera-se um jogo de informação incompleta, uma vez que os agentes não tem informações sobre as estratégias de outros agentes. Para o processo de aprendizado de estratégias, utiliza-se um algoritmo evolutivo, no qual os agentes visando maximizar a sua função de fitness, atuam como autorregulares dos processos de trocas possibilitadas pelo jogo, contribuindo para o aumento do numero de interações bem sucedidas. São analisados 5 diferentes casos de composição da sociedade. Para alguns casos, analisa-se também um segundo tipo de cenário, onde a topologia de rede é modificada, representando algum tipo de mobilidade, a fim de analisar se os resultados são dependentes da vizinhança. Alem disso, um terceiro cenário é estudado, no qual é se determinada uma política de influencia, quando as medias dos parâmetros que definem as estratégias adotadas pelos agentes tornam-se publicas em alguns momentos da simulação, e os agentes que adotam a mesma estratégia de troca, influenciados por isso, imitam esses valores. O modelo foi implementado em NetLogo.

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Human operators are unique in their decision making capability, judgment and nondeterminism. Their sense of judgment, unpredictable decision procedures, susceptibility to environmental elements can cause them to erroneously execute a given task description to operate a computer system. Usually, a computer system is protected against some erroneous human behaviors by having necessary safeguard mechanisms in place. But some erroneous human operator behaviors can lead to severe or even fatal consequences especially in safety critical systems. A generalized methodology that can allow modeling and analyzing the interactions between computer systems and human operators where the operators are allowed to deviate from their prescribed behaviors will provide a formal understanding of the robustness of a computer system against possible aberrant behaviors by its human operators. We provide several methodology for assisting in modeling and analyzing human behaviors exhibited while operating computer systems. Every human operator is usually given a specific recommended set of guidelines for operating a system. We first present process algebraic methodology for modeling and verifying recommended human task execution behavior. We present how one can perform runtime monitoring of a computer system being operated by a human operator for checking violation of temporal safety properties. We consider the concept of a protection envelope giving a wider class of behaviors than those strictly prescribed by a human task that can be tolerated by a system. We then provide a framework for determining whether a computer system can maintain its guarantees if the human operators operate within their protection envelopes. This framework also helps to determine the robustness of the computer system under weakening of the protection envelopes. In this regard, we present a tool called Tutela that assists in implementing the framework. We then examine the ability of a system to remain safe under broad classes of variations of the prescribed human task. We develop a framework for addressing two issues. The first issue is: given a human task specification and a protection envelope, will the protection envelope properties still hold under standard erroneous executions of that task by the human operators? In other words how robust is the protection envelope? The second issue is: in the absence of a protection envelope, can we approximate a protection envelope encompassing those standard erroneous human behaviors that can be safely endured by the system? We present an extension of Tutela that implements this framework. The two frameworks mentioned above use Concurrent Game Structures (CGS) as models for both computer systems and their human operators. However, there are some shortcomings of this formalism for our uses. We add incomplete information concepts in CGSs to achieve better modularity for the players. We introduce nondeterminism in both the transition system and strategies of players and in the modeling of human operators and computer systems. Nondeterministic action strategies for players in \emph{i}ncomplete information \emph{N}ondeterministic CGS (iNCGS) is a more precise formalism for modeling human behaviors exhibited while operating a computer system. We show how we can reason about a human behavior satisfying a guarantee by providing a semantics of Alternating Time Temporal Logic based on iNCGS player strategies. In a nutshell this dissertation provides formal methodology for modeling and analyzing system robustness against both expected and erroneous human operator behaviors.

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Matching theory and matching markets are a core component of modern economic theory and market design. This dissertation presents three original contributions to this area. The first essay constructs a matching mechanism in an incomplete information matching market in which the positive assortative match is the unique efficient and unique stable match. The mechanism asks each agent in the matching market to reveal her privately known type. Through its novel payment rule, truthful revelation forms an ex post Nash equilibrium in this setting. This mechanism works in one-, two- and many-sided matching markets, thus offering the first mechanism to unify these matching markets under a single mechanism design framework. The second essay confronts a problem of matching in an environment in which no efficient and incentive compatible matching mechanism exists due to matching externalities. I develop a two-stage matching game in which a contracting stage facilitates subsequent conditionally efficient and incentive compatible Vickrey auction stage. Infinite repetition of this two-stage matching game enforces the contract in every period. This mechanism produces inequitably distributed social improvement: parties to the contract receive all of the gains and then some. The final essay demonstrates the existence of prices which stably and efficiently partition a single set of agents into firms and workers, and match those two sets to each other. This pricing system extends Kelso and Crawford's general equilibrium results in a labor market matching model and links one- and two-sided matching markets as well.

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Doutoramento em Economia.

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On the one hand, pesticides may be absorbed into the body orally, dermally, ocularly and by inhalation and the human exposure may be dietary, recreational and/or occupational where toxicity could be acute or chronic. On the other hand, the environmental fate and toxicity of the pesticide is contingent on the physico-chemical characteristics of pesticide, the soil composition and adsorption. Human toxicity is also dependent on the exposure time and individual’s susceptibility. Therefore, this work will focus on the development of an Artificial Intelligence based diagnosis support system to assess the pesticide toxicological risk to humanoid, built under a formal framework based on Logic Programming to knowledge representation and reasoning, complemented with an approach to computing grounded on Artificial Neural Networks. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.

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This thesis consists of three self-contained essays on nonlinear pricing and rent-seeking. In the first chapter of the thesis, I provide new theoretical insights about non-linear pricing in monopoly and common agency by combining the principal-agent framework with other-regarding preferences. I introduce a new theoretical model that separately characterizes status-seeker and inequity-averse buyers. I show how the buyer’s optimal choice of quality and market inefficiency change when the buyer has other-regarding preferences. In the second chapter, I find the optimal productive rent-seeking and sabotaging efforts when the prize is endogenous. I show that due to the existence of endogeneity, sabotaging the productive rent-seeking efforts causes sabotaging the endogenous part of the prize, which can affect the rent-seeking efforts. Moreover, I introduce social preferences into my model and characterize symmetric productive rent-seeking and sabotaging efforts. In the last chapter, I propose a new theoretical model regarding information disclosure with Bayesian persuasion in rent-seeking contests when the efforts are productive. I show that under one-sided incomplete information, information disclosure decision depends on both the marginal costs of efforts and the marginal benefit of aggregate exerted effort. I find that since the efforts are productive and add a positive surplus on the fixed rent, my model narrows down the conditions for the information disclosure compared to the exogenous model. Under the two-sided incomplete information case, I observe that there is a non-monotone relationship between optimal effort and posterior beliefs. Thus, it might be difficult to conclude whether a contest organizer should disclose any information to contestants.

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Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

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Our previous studies indicate that oxycodone is a putative kappa-opioid agonist, whereas morphine is a well documented mu-opioid agonist. Because there is limited information regarding the development of tolerance to oxycodone, this study was designed to 1) document the development of tolerance to the antinociceptive effects of chronically infused i.v. oxycodone relative to that for i.v. morphine and 2) quantify the degree of antinociceptive cross-tolerance between morphine and oxycodone in adult male Dark Agouti (DA) rats. Antinociceptive testing was performed using the tail-flick latency test. Complete antinociceptive tolerance was achieved in 48 to 84 h after chronic infusion of equi-antinociceptive doses of i.v. oxycodone (2.5 mg/24 h and 5 mg/24 h) and i.v. morphine (10 mg/24 h and 20 mg/24 h, respectively). Dose-response curves for bolus doses of i.v. and i.c.v. morphine and oxycodone were produced in naive, morphine-tolerant, and oxycodone-tolerant rats. Consistent with our previous findings that oxycodone and morphine produce their intrinsic antinociceptive effects through distinctly different opioid receptor populations, there was no discernible cross-tolerance when i.c.v. oxycodone was given to morphine-tolerant rats. Similarly, only a low degree of cross-tolerance (approximate to 24%) was observed after i.v. oxycodone administration to morphine-tolerant rats. By contrast, both i.v. and i.c.v. morphine showed a high degree of cross-tolerance (approximate to 71% and approximate to 54%, respectively) in rats rendered tolerant to oxycodone. Taken together, these findings suggest that, after parenteral but not supraspinal administration, oxycodone is metabolized to a mu-opioid agonist metabolite, thereby explaining asymmetric and incomplete cross-tolerance between oxycodone and morphine.

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When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

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This paper studies experimentally how the existence of social information networks affects the ways in which firms recruit new personnel. Through such networks firms learn about prospective employees' performance in previous jobs. Assuming individualistic preferences social networks are predicted not to affect overall labor market behavior, while with social preferences the prediction is that when bilaterally negotiated: (i) wages will be higher and (ii) that workers in jobs with incomplete contracts will respond with higher effort. Our experimental results are consistent with the social preferences view, both for the case of excess demand and excess supply of labor. In particular, the presence of information networks leads to more efficient allocations.

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In this study we elicit agents’ prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis.

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\documentstyle[portada,11pt]{article}This paper shows that the presence of private information in aneconomy can be a source of market incompleteness even when it is feasibleto issue a set of securities that completely eliminates the informationalasymmetries in equilibrium. We analyze a simple security design model in which avolume maximizing futures exchange chooses not only the characteristics ofeach individual contract but also the number of contracts. Agents have rationalexpectations and differ in information, endowments and, possibly, attitudestoward risk. The emergence of complete or incomplete markets in equilibriumdepends on whether the {\it adverse selection effect} is stronger or weakerthan the {\it Hirshleifer effect}, as new securitiesare issued and prices reveal more information. When the Hirshleifer effectdominates, the exchange chooses an incomplete set of financial contracts, andthe equilibrium price is partially revealing.