985 resultados para Incomplete information
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In this thesis, we extend some ideas of statistical physics to describe the properties of human mobility. By using a database containing GPS measures of individual paths (position, velocity and covered space at a spatial scale of 2 Km or a time scale of 30 sec), which includes the 2% of the private vehicles in Italy, we succeed in determining some statistical empirical laws pointing out "universal" characteristics of human mobility. Developing simple stochastic models suggesting possible explanations of the empirical observations, we are able to indicate what are the key quantities and cognitive features that are ruling individuals' mobility. To understand the features of individual dynamics, we have studied different aspects of urban mobility from a physical point of view. We discuss the implications of the Benford's law emerging from the distribution of times elapsed between successive trips. We observe how the daily travel-time budget is related with many aspects of the urban environment, and describe how the daily mobility budget is then spent. We link the scaling properties of individual mobility networks to the inhomogeneous average durations of the activities that are performed, and those of the networks describing people's common use of space with the fractional dimension of the urban territory. We study entropy measures of individual mobility patterns, showing that they carry almost the same information of the related mobility networks, but are also influenced by a hierarchy among the activities performed. We discover that Wardrop's principles are violated as drivers have only incomplete information on traffic state and therefore rely on knowledge on the average travel-times. We propose an assimilation model to solve the intrinsic scattering of GPS data on the street network, permitting the real-time reconstruction of traffic state at a urban scale.
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Using survey and interview data gathered from educators and educational administrators, we investigate school and community impacts of unconventional gas extraction within Pennsylvania's Marcellus Shale region. Respondents in areas with high levels of drilling are significantly more likely to perceive the effects of local economic gains, but also report increased inequality, heightened vulnerability of disadvantaged community members, and pronounced strains on local infrastructure. As community stakeholders in positions of local leadership, school leaders in areas experiencing Marcellus Shale natural gas extraction often face multiple decision-making dilemmas. These dilemmas occur in the context of incomplete information and rapid, unpredictable community change involving the emergence of both new opportunities and new insecurities.
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In estimation of a survival function, current status data arises when the only information available on individuals is their survival status at a single monitoring time. Here we briefly review extensions of this form of data structure in two directions: (i) doubly censored current status data, where there is incomplete information on the origin of the failure time random variable, and (ii) current status information on more complicated stochastic processes. Simple examples of these data forms are presented for motivation.
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Increasing commercial pressures on land are provoking fundamental and far-reaching changes in the relationships between people and land. Much knowledge on land-oriented investments projects currently comes from the media. Although this provides a good starting point, lack of transparency and rapidly changing contexts mean that this is often unreliable. The International Land Coalition, in partnership with Oxfam Novib, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), University of Pretoria, Centre for Development and Environment of the University of Bern (CDE), and GIZ, started to compile an inventory of land-related investments. This project aims to better understand the extent, trends and impacts of land-related investments by supporting an ongoing and systematic stocktaking exercise of the various investment projects currently taking place worldwide. It involves a large number of organizations and individuals working in areas where land transactions are being made, and able to provide details of such investments. The project monitors land transactions in rural areas that imply a transformation of land use rights from communities and smallholders to commercial use, and are made both by domestic and foreign investors (private actors, governments, government-back private investors). The focus is on investments for food or agrofuel production, timber extraction, carbon trading, mineral extraction, conservation and tourism. A novel way of using ITC to document land acquisitions in a spatially explicit way and by using an approach called “crowdsourcing” is being developed. This approach will allow actors to share information and knowledge directly and at any time on a public platform, where it will be scrutinized in terms of reliability and cross checked with other sources. Up to now, over 1200 deals have been recorded across 96 countries. Details of such transactions have been classified in a matrix and distributed to over 350 contacts worldwide for verification. The verified information has been geo-referenced and represented in two global maps. This is an open database enabling a continued monitoring exercise and the improvement of data accuracy. More information will be released over time. The opportunities arise from overcoming constraints by incomplete information by proposing a new way of collecting, enhancing and sharing information and knowledge in a more democratic and transparent manner. The intention is to develop interactive knowledge platform where any interested person can share and access information on land deals, their link to involved stakeholders, and their embedding into a geographical context. By making use of new ICT technologies that are more and more in the reach of local stakeholders, as well as open access and web-based spatial information systems, it will become possible to create a dynamic database containing spatial explicit data. Feeding in data by a large number of stakeholders, increasingly also by means of new mobile ITC technologies, will open up new opportunities to analyse, monitor and assess highly dynamic trends of land acquisition and rural transformation.
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Decision strategies aim at enabling reasonable decisions in cases of uncertain policy decision problems which do not meet the conditions for applying standard decision theory. This paper focuses on decision strategies that account for uncertainties by deciding whether a proposed list of policy options should be accepted or revised (scope strategies) and whether to decide now or later (timing strategies). They can be used in participatory approaches to structure the decision process. As a basis, we propose to classify the broad range of uncertainties affecting policy decision problems along two dimensions, source of uncertainty (incomplete information, inherent indeterminacy and unreliable information) and location of uncertainty (information about policy options, outcomes and values). Decision strategies encompass multiple and vague criteria to be deliberated in application. As an example, we discuss which decision strategies may account for the uncertainties related to nutritive technologies that aim at reducing methane (CH4) emissions from ruminants as a means of mitigating climate change, limiting our discussion to published scientific information. These considerations not only speak in favour of revising rather than accepting the discussed list of options, but also in favour of active postponement or semi-closure of decision-making rather than closure or passive postponement.
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We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.
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In the setting of noncooperative game theory, strategic negligibility of individual agents, or diffuseness of information, has been modeled as a nonatomic measure space, typically the unit interval endowed with Lebesgue measure. However, recent work has shown that with uncountable action sets, for example the unit interval, there do not exist pure-strategy Nash equilibria in such nonatomic games. In this brief announcement, we show that there is a perfectly satisfactory existence theory for nonatomic games provided this nonatomicity is formulated on the basis of a particular class of measure spaces, hyperfinite Loeb spaces. We also emphasize other desirable properties of games on hyperfinite Loeb spaces, and present a synthetic treatment, embracing both large games as well as those with incomplete information.
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Стефанка Чукова, Хър Гуан Тео - В това изследване разглеждаме и разширяваме предишната ни работа по цензуриране, типично за авто гаранционни данни. За да разрешим проблема с непълната информация за километража, използваме линеен подход в непараметрични рамки. Оценяваме средните кумулативни гаранционни разходи (за превозно средство) и стандартната им грешка като функция на възрастта, на километража и на реалното (календарно) време.
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As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.
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AMS subject classification: 90C31, 90A09, 49K15, 49L20.
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2000 Mathematics Subject Classi cation: Primary 90C31. Secondary 62C12, 62P05, 93C41.
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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 de�fined. Pint�er 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 de�ne 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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When modeling game situations of incomplete information one usually considers the players’ hierarchies of beliefs, a source of all sorts of complications. Harsányi (1967-68)’s idea henceforth referred to as the ”Harsányi program” is that hierarchies of beliefs can be replaced by ”types”. The types constitute the ”type space”. In the purely measurable framework Heifetz and Samet (1998) formalize the concept of type spaces and prove the existence and the uniqueness of a universal type space. Meier (2001) shows that the purely measurable universal type space is complete, i.e., it is a consistent object. With the aim of adding the finishing touch to these results, we will prove in this paper that in the purely measurable framework every hierarchy of beliefs can be represented by a unique element of the complete universal type space.
Resumo:
Several game theoretical topics require the analysis of hierarchical beliefs, particularly in incomplete information situations. For the problem of incomplete information, Hars´anyi suggested the concept of the type space. Later Mertens & Zamir gave a construction of such a type space under topological assumptions imposed on the parameter space. The topological assumptions were weakened by Heifetz, and by Brandenburger & Dekel. In this paper we show that at very natural assumptions upon the structure of the beliefs, the universal type space does exist. We construct a universal type space, which employs purely a measurable parameter space structure.
Resumo:
Ordinary type spaces (Heifetz and Samet, 1998) are essential ingredients of incomplete information games. With ordinary type spaces one can grab the notions of beliefs, belief hierarchies and common prior etc. However, ordinary type spaces cannot handle the notions of finite belief hierarchy and unawareness among others. In this paper we consider a generalization of ordinary type spaces, and introduce the so called generalized type spaces which can grab all notions ordinary type spaces can and more, finite belief hierarchies and unawareness among others. We also demonstrate that the universal generalized type space exists.