914 resultados para Markov decision process (POMDP)


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Before signing electronic contracts, a rational agent should estimate the expected utilities of these contracts and calculate the violation risks related to them. In order to perform such pre-signing procedures, this agent has to be capable of computing a policy taking into account the norms and sanctions in the contracts. In relation to this, the contribution of this work is threefold. First, we present the Normative Markov Decision Process, an extension of the Markov Decision Process for explicitly representing norms. In order to illustrate the usage of our framework, we model an example in a simulated aerospace aftermarket. Second, we specify an algorithm for identifying the states of the process which characterize the violation of norms. Finally, we show how to compute policies with our framework and how to calculate the risk of violating the norms in the contracts by adopting a particular policy.

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In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

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Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

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Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

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Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

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Työn tavoitteena oli selvittää organisaation ostopäätösprosessi, kun tuotteina ovat biohajoavat kasvo- ja kallokirurgian implantit. Ensin selvitettiin biohajoavien implanttien markkinapotentiaalia, biohajoavien materiaalien lisäksi implanttien valmistuksessa käytettäviä muita materiaaleja sekä implanteilta vaadittavia ominaisuuksia kirjallisuuden ja internetin sekä asiantuntijahaastatteluiden avulla. Kirjallisuuden avulla selvitettiin myös organisaatioiden ostopäätösprosessien yleisiä piirteitä ja vaiheita. Biohajoavien kasvo- ja kallokirurgian implanttien ostopäätösprosessia tutkittiin kirjallisen kyselytutkimuksen avulla, joka oli suunnattu alan asiantuntijoille Euroopassa, Yhdysvalloissa sekä Kanadassa. Tutkimuksessa selvitettiin mm. tärkeimpiä käytettävien implanttien materiaalivalintaan vaikuttavia kriteereitä, ostopäätösprosessiin osallistuvia organisaation jäseniä, sekä heidän roolejaan päätöksenteossa, implantteja koskevan informaation etsintää sekä ostopäätösprosessin vaiheita. Kirjallisuudesta, internetistä, asiantuntijahaastatteluista ja kyselytutkimuksesta saatu tieto koottiin vuokaaviomalliksi, joka kuvaa kasvo- ja kallokirurgian implanttien ostopäätösprosessia organisaatioissa. Lopuksi esitettiin myös ehdotuksia markkinointisuunnitelmaan sekä jatkotutkimusehdotukset.

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Corporate governance has been in the spotlight for the past two decades, being subject of numerous researches all over the world. Governance is pictured as a broad and diverse theme, evolving through different routes to form distinct systems. This scenario together with 2 types of agency problems (investor vs. management and minorities vs. controlling shareholders) produce different definitions for governance. Usually, studies investigate whether corporate governance structures influence firm performance, and company valuation. This approach implies investors can identify those impacts and later take them into consideration when making investment decisions. However, behavioral finance theory shows that not always investors take rational decisions, and therefore the modus operandi of those professionals needs to be understood. So, this research aimed to investigate to what extent Brazilian corporate governance standards and practices influence the investment decision-making process of equity markets' professionals from the sell-side and buy-side. This exploratory study was carried out through qualitative and quantitative approaches. In the qualitative phase, 8 practitioners were interviewed and 3 dimensions emerged: understanding, pertinence and practice. Based on the interviews’ findings, a questionnaire was formulated and distributed to buy-siders and sell-siders that cover Brazilian stocks. 117 respondents from all over the world contributed to the study. The data obtained were analyzed through structural equation modeling and descriptive statistics. The 3 dimensions became 5 constructs: definition (institutionalized governance, informal governance), pertinence (relevance), practice (valuation process, structured governance assessment) The results of this thesis suggest there is no definitive answer, as the extent to which governance will influence an investment decision process will depend on a number of circumstances which compose the context. The only certainty is the need to present a “corporate governance behavior”, rather than simply establishing rules and regulations at firm and country level.

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ABSTRACT: The femtocell concept aims to combine fixed-line broadband access with mobile telephony using the deployment of low-cost, low-power third and fourth generation base stations in the subscribers' homes. While the self-configuration of femtocells is a plus, it can limit the quality of service (QoS) for the users and reduce the efficiency of the network, based on outdated allocation parameters such as signal power level. To this end, this paper presents a proposal for optimized allocation of users on a co-channel macro-femto network, that enable self-configuration and public access, aiming to maximize the quality of service of applications and using more efficiently the available energy, seeking the concept of Green networking. Thus, when the user needs to connect to make a voice or a data call, the mobile phone has to decide which network to connect, using the information of number of connections, the QoS parameters (packet loss and throughput) and the signal power level of each network. For this purpose, the system is modeled as a Markov Decision Process, which is formulated to obtain an optimal policy that can be applied on the mobile phone. The policy created is flexible, allowing different analyzes, and adaptive to the specific characteristics defined by the telephone company. The results show that compared to traditional QoS approaches, the policy proposed here can improve energy efficiency by up to 10%.

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O uso da comunicação de voz e dados através de dispositivos móveis vem aumentando significativamente nos últimos anos. Tal expansão traz algumas dificuldades inerentes, tais como: ampliação constante de capacidade das redes e eficiência energética. Neste contexto, vem se consolidando o conceito de Green networks, que se concentra no esforço para economia de energia e redução de CO2. Neste sentido, este trabalho propõe validar um modelo de uma política baseado em processo markoviano de decisão, visando a otimizar o consumo de energia, QoS e QoE, na alocação de usuários em redes macrocell e femtocell. Para isso o modelo foi inserido no simulador NS-2, aliando a solução analítica markoviana à flexibilidade característica da simulação discreta. A partir dos resultados apresentados na simulação, a política obteve uma economia significativa no consumo energético, melhorando a eficiência energética em até 4%, além de melhorar a qualidade de serviço em relação às redes macrocell e femtocell, demonstrando-se eficaz, de modo a alterar diretamente as métricas de QoS e de QoE.

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This paper studies the average control problem of discrete-time Markov Decision Processes (MDPs for short) with general state space, Feller transition probabilities, and possibly non-compact control constraint sets A(x). Two hypotheses are considered: either the cost function c is strictly unbounded or the multifunctions A(r)(x) = {a is an element of A(x) : c(x, a) <= r} are upper-semicontinuous and compact-valued for each real r. For these two cases we provide new results for the existence of a solution to the average-cost optimality equality and inequality using the vanishing discount approach. We also study the convergence of the policy iteration approach under these conditions. It should be pointed out that we do not make any assumptions regarding the convergence and the continuity of the limit function generated by the sequence of relative difference of the alpha-discounted value functions and the Poisson equations as often encountered in the literature. (C) 2012 Elsevier Inc. All rights reserved.

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In this research project, I have integrated two research streams on international strategic decisions making in international firms: upper echelons or top management teams (TMT) internationalization research and international strategic decision making process research. Both research streams in international business literature have evolved independently, but there is a potential in combining these two streams of research. The first empirical paper “TMT internationalization and international strategic decision making process: a decision level analysis of rationality, speed, and performance” explores the influence of TMT internationalization on strategic decision rationality and speed and, subsequently, their effect on international strategic decision effectiveness (performance). The results show that the internationalization of TMT is positively related to decision effectiveness and this relationship is mediated by decision rationality while the hypotheses regarding the association between TMT internationalization and decision speed, and the mediating effect of speed were not supported. The second paper “TMT internationalization and international strategic decision rationality: the mediating role of international information” of my thesis is a simple but logical extension of first paper. The first paper showed that TMT Internationalization has a significant positive effect on international strategic decision rationality. The second paper explicitly showed that TMT internationalization affect on international strategic decision rationality comes from two sources: international experience (personal international knowledge and information) and international information collected from managerial international contacts. For this research project, I have collected data from international software firms in Pakistan. My research contributes to the literature on upper echelons theory and strategic decision making in context of international business and international firms by explicitly examining the link between TMT internationalization and characteristics of strategic decisions making process (i.e. rationality and speed) in international firms and their possible mediating effect on performance.

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We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in large state spaces. We provide a mean-square-error performance analysis under constant step-sizes. The gain of cooperation in the form of more stability and less bias and variance in the prediction error, is illustrated in the context of a classical model. We show that the improvement in performance is especially significant when the behavior policy of the agents is different from the target policy under evaluation.