1,120 research outputs found

    Recovering Incedence Functions

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    Assignment Methods for Incidence Calculus

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    AbstractIncidence calculus is a mechanism for probabilistic reasoning in which sets of possible worlds, called incidences, are associated with axioms, and probabilities are then associated with these sets. Inference rules are used to deduce bounds on the incidence of formulae which are not axioms, and bounds for the probability of such a formula can then be obtained. In practice an assignment of probabilities directly to axioms may be given, and it is then necessary to find an assignment of incidence which will reproduce these probabilities. We show that this task of assigning incidences can be viewed as a tree searching problem, and two techniques for performing this research are discussed. One of these is a new proposal involving a depth first search, while the other incorporates a random element. A Prolog implementation of these methods has been developed. The two approaches are compared for efficiency and the significance of their results are discussed. Finally we discuss a new proposal for applying techniques from linear programming to incidence calculus

    Metaphysics and Law

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    The dichotomy between questions of fact and questions of law serves as a starting point for the following discussion of the nature of legal reasoning. In the course of the dialogue the author notes similarities and dissimilarities between legal reasoning and philosophical and mathematical reasoning. In the end we are left with a clearer insight into the distinctive features of the adjudicative process

    Extended incidence calculus and its comparison with related theories

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    This thesis presents a comprehensive study o f incidence calculus, a probabilistic logic for reasoning under uncertainty which extends two-value propositional logic to a multiple-value logic. There are three main contributions in this thesis.First of all, the original incidence calculus is extended considerably in three aspects: (a) the original incidence calculus is generalized; (b) an efficient algorithm for incidence assignment based on generalized incidence calculus is developed; (c) a combination rule is proposed for the combination of both independent and some dependent pieces of evidence. Extended incidence calculus has the advantages of representing information flexibly and combining multiple sources o f evidence.Secondly, a comprehensive comparison between extended incidence calculus and the Dempster-Shafer (DS) theory of evidence is provided. It is proved that extended incidence calculus is equivalent to DS theory in representing evidence and combining independent evidence but superior to DS theory in combining de­pendent evidence.Thirdly, the relations between extended incidence calculus and the assumption- based truth maintenance systems are discussed. It is proved that extended inci­dence calculus is equivalent to the ATM S in calculating labels for nodes. Extended incidence calculus can also be used as a basis for constructing probabilistic ATMSs.The study in this thesis reveals that extended incidence calculus can be re­garded as a bridge between numerical and symbolic reasoning mechanisms

    The Method of Assigning Incidences

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    Formal methods and digital systems validation for airborne systems

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    This report has been prepared to supplement a forthcoming chapter on formal methods in the FAA Digital Systems Validation Handbook. Its purpose is as follows: to outline the technical basis for formal methods in computer science; to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used on board aircraft; and to suggest factors for consideration when formal methods are offered in support of certification. These latter factors assume the context for software development and assurance described in RTCA document DO-178B, 'Software Considerations in Airborne Systems and Equipment Certification,' Dec. 1992

    Incidence Calculus: A Mechanism for Probabilistic Reasoning

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    Mechanisms for the automation of uncertainty are required for expert systems. Sometimes these mechanisms need to obey the properties of probabilistic reasoning. We argue that a purely numeric mechanism, like those proposed so far, cannot provide a probabilistic logic with truth functional connec- tives. We propose an alternative mechanism, Incidence Calculus, which is based on a representation of uncertainty using sets of points, which might represent situations models or possible worlds. Incidence Calculus does provide a probabilistic logic with truth functional connectives

    A source modelling system and its use for uncertainty management

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    Human agents have to deal with a considerable amount of information from their environment and are also continuously faced with the need to take actions. As that information is largely of an uncertain nature, human agents have to decide whether, or how much, to believe individual pieces of information. To enable a reasoning system to deal in general with the demands of a real environment, and with information from human sources in particular, requires tools for uncertainty management and belief formation. This thesis presents a model for the management of uncertain information from human sources. Dealing, more specifically, with information which has been pre-processed by a natural language processor and transformed into an event-based representation, the model assesses information, forms beliefs and resolves conflicts between them in order to maintain a consistent world model. The approach is built on the fundamental principle that the uncertainty of information from people can, in the majority of situations, successfully be assessed through source models which record factors concerning the source's abilities and trustworthiness. These models are adjusted to reflect changes in the behaviour of the source. A mechanism is presented together with the underlying principles to reproduce such a behaviour. A high-level design is also given to make the proposed model reconstructible, and the successful operation of the model is demonstrated on two detailed examples
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