13 resultados para Quantified Default Logic
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After a historical introduction, the bulk of the thesis concerns the study of a declarative semantics for logic programs. The main original contributions are: ² WFSX (Well–Founded Semantics with eXplicit negation), a new semantics for logic programs with explicit negation (i.e. extended logic programs), which compares favourably in its properties with other extant semantics. ² A generic characterization schema that facilitates comparisons among a diversity of semantics of extended logic programs, including WFSX. ² An autoepistemic and a default logic corresponding to WFSX, which solve existing problems of the classical approaches to autoepistemic and default logics, and clarify the meaning of explicit negation in logic programs. ² A framework for defining a spectrum of semantics of extended logic programs based on the abduction of negative hypotheses. This framework allows for the characterization of different levels of scepticism/credulity, consensuality, and argumentation. One of the semantics of abduction coincides with WFSX. ² O–semantics, a semantics that uniquely adds more CWA hypotheses to WFSX. The techniques used for doing so are applicable as well to the well–founded semantics of normal logic programs. ² By introducing explicit negation into logic programs contradiction may appear. I present two approaches for dealing with contradiction, and show their equivalence. One of the approaches consists in avoiding contradiction, and is based on restrictions in the adoption of abductive hypotheses. The other approach consists in removing contradiction, and is based in a transformation of contradictory programs into noncontradictory ones, guided by the reasons for contradiction.
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em Informática
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Pascoa and Seghir (2009) noticed that when collateralized promises become subject to utility penalties on default, Ponzi schemes may occur. However, equilibrium exists in some interesting cases. Under low penalties, equilibrium exists if the collateral does not yield utility (for example, when it is a productive asset or a security). Equilibrium exists also under more severe penalties and collateral utility gains, when the promise or the collateral are nominal assets and the margin requirements are endogenous: relative inflation rates and margin coefficients can make the income effects dominate the penalty effects. An equilibrium refinement avoids no-trade equilibria with unduly repayment beliefs. Our refinement differs from the one used by Dubey, Geanakoplos and Shubik (2005) as it does not eliminate no trade equilibria whose low delivery rates are consistent with the propensity to default of agents that are on the verge of selling.
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Dissertação para obtenção do Grau de Doutor em Matemática - Lógica e Fundamentos da Matemática
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Ontologies formalized by means of Description Logics (DLs) and rules in the form of Logic Programs (LPs) are two prominent formalisms in the field of Knowledge Representation and Reasoning. While DLs adhere to the OpenWorld Assumption and are suited for taxonomic reasoning, LPs implement reasoning under the Closed World Assumption, so that default knowledge can be expressed. However, for many applications it is useful to have a means that allows reasoning over an open domain and expressing rules with exceptions at the same time. Hybrid MKNF knowledge bases make such a means available by formalizing DLs and LPs in a common logic, the Logic of Minimal Knowledge and Negation as Failure (MKNF). Since rules and ontologies are used in open environments such as the Semantic Web, inconsistencies cannot always be avoided. This poses a problem due to the Principle of Explosion, which holds in classical logics. Paraconsistent Logics offer a solution to this issue by assigning meaningful models even to contradictory sets of formulas. Consequently, paraconsistent semantics for DLs and LPs have been investigated intensively. Our goal is to apply the paraconsistent approach to the combination of DLs and LPs in hybrid MKNF knowledge bases. In this thesis, a new six-valued semantics for hybrid MKNF knowledge bases is introduced, extending the three-valued approach by Knorr et al., which is based on the wellfounded semantics for logic programs. Additionally, a procedural way of computing paraconsistent well-founded models for hybrid MKNF knowledge bases by means of an alternating fixpoint construction is presented and it is proven that the algorithm is sound and complete w.r.t. the model-theoretic characterization of the semantics. Moreover, it is shown that the new semantics is faithful w.r.t. well-studied paraconsistent semantics for DLs and LPs, respectively, and maintains the efficiency of the approach it extends.
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This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.
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Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.
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This study attempts to identify basis-trading opportunities in the European banking sector by comparing two different measures for the market’s assessment of risk: market-observed CDS spreads and model-implied Z-spreads. Using a sample of 10 banks, over a period of 3 years following the European banking crisis, it can be concluded that there were arbitrage opportunities in the sector, as evidenced by the derived negative bases.
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This paper extends the model of Spolaore (2004) about adjustments in di erent government systems for the context of scal adjustments and sovereign default. We introduce asymmetry between groups in income and preferences towards scal reforms. Default a ects di erently each group and becomes a possibility if reforms are not enacted after public nance solvency shocks, in uencing the political game according to its likelihood. With the extensions, new situations which were not possible with the previous framework arise. After the exposition of the model, the Argentine default in 2001 provides an example of the political con icts addressed by the model.
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The amorphous silicon photo-sensor studied in this thesis, is a double pin structure (p(a-SiC:H)-i’(a-SiC:H)-n(a-SiC:H)-p(a-SiC:H)-i(a-Si:H)-n(a-Si:H)) sandwiched between two transparent contacts deposited over transparent glass thus with the possibility of illumination on both sides, responding to wave-lengths from the ultra-violet, visible to the near infrared range. The frontal il-lumination surface, glass side, is used for light signal inputs. Both surfaces are used for optical bias, which changes the dynamic characteristics of the photo-sensor resulting in different outputs for the same input. Experimental studies were made with the photo-sensor to evaluate its applicability in multiplexing and demultiplexing several data communication channels. The digital light sig-nal was defined to implement simple logical operations like the NOT, AND, OR, and complex like the XOR, MAJ, full-adder and memory effect. A pro-grammable pattern emission system was built and also those for the validation and recovery of the obtained signals. This photo-sensor has applications in op-tical communications with several wavelengths, as a wavelength detector and to execute directly logical operations over digital light input signals.
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Repercussions of innovation adoption and diffusion studies have long been imperative to the success of novel introductions. However, perceptions and deductions of current innovation understandings have been changing over time. The paradigm shift from the goods-dominant (G-D) logic to the service-dominant (S-D) logic potentially makes the distinction between product (goods) innovation and service innovation redundant as the S-D logic lens views all innovations as service innovations (Vargo and Lusch, 2004; 2008; Lusch and Nambisan, 2015). From this perspective, product innovations are in essence service innovations, as goods serve as mere distribution mechanisms to deliver service. Nonetheless, the transition to such a broadened and transcending view of service innovation necessitates concurrently a change in the underlying models used to investigate innovation and its subsequent adoption. The present research addresses this gap by engendering a novel model for the most crucial period of service diffusion within the S-D logic context – the post-initial adoption phase, which demarcates an individual’s behavior after the initial adoption decision of a service. As a wellfounded understanding of service diffusion and the complementary innovation adoption still lingers in its infancy, the current study develops a model based on interdisciplinary domains mapping. Here fore, knowledge of the relatively established viral source domain is mapped to the comparatively undetermined target domain of service innovation adoption. To assess the model and test the importance of the explanatory variables, survey data from 750 respondents of a bank in Northern Germany is scrutinized by means of Structural Equation Modeling (SEM). The findings reveal that the continuance intention of a customer, actual usage of the service and the customer influencer value all constitute important postinitial adoption behavior that have meaningful implications for a successful service adoption. Second, the four constructs customer influencer value, organizational commitment, perceived usefulness and service customization are evidenced to have a differential impact on a iv customer’s post-initial adoption behavior. Third, this study indicates that post-initial adoption behavior further underlies the influence of a user’s age and besides that is also provoked by the internal and external environments of service adoption. Finally, this research amalgamates the broad view of service innovation by Nambisan and Lusch (2015) with the findings ensuing this enquiry’s model to arrive at a framework that it both, generalizable and practically applicable. Implications for academia and practitioners are captured along with avenues for future research.