16 resultados para reasoning biases

em University of Queensland eSpace - Australia


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We utilize anthropic reasoning to demonstrate that we are typical observers of our reference class under a self-sampling assumption by investigating the definition of what a civilization is. With reference to the conflict between such reasoning and the observational lack of extra-terrestrial intelligent life, we conclude that a part of our theoretical understanding of the Universe will be at fault.

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Assessments for assigning the conservation status of threatened species that are based purely on subjective judgements become problematic because assessments can be influenced by hidden assumptions, personal biases and perceptions of risks, making the assessment process difficult to repeat. This can result in inconsistent assessments and misclassifications, which can lead to a lack of confidence in species assessments. It is almost impossible to Understand an expert's logic or visualise the underlying reasoning behind the many hidden assumptions used throughout the assessment process. In this paper, we formalise the decision making process of experts, by capturing their logical ordering of information, their assumptions and reasoning, and transferring them into a set of decisions rules. We illustrate this through the process used to evaluate the conservation status of species under the NatureServe system (Master, 1991). NatureServe status assessments have been used for over two decades to set conservation priorities for threatened species throughout North America. We develop a conditional point-scoring method, to reflect the current subjective process. In two test comparisons, 77% of species' assessments using the explicit NatureServe method matched the qualitative assessments done subjectively by NatureServe staff. Of those that differed, no rank varied by more than one rank level under the two methods. In general, the explicit NatureServe method tended to be more precautionary than the subjective assessments. The rank differences that emerged from the comparisons may be due, at least in part, to the flexibility of the qualitative system, which allows different factors to be weighted on a species-by-species basis according to expert judgement. The method outlined in this study is the first documented attempt to explicitly define a transparent process for weighting and combining factors under the NatureServe system. The process of eliciting expert knowledge identifies how information is combined and highlights any inconsistent logic that may not be obvious in Subjective decisions. The method provides a repeatable, transparent, and explicit benchmark for feedback, further development, and improvement. (C) 2004 Elsevier SAS. All rights reserved.

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If two images are shown in rapid sequential order, they are perceived as a single, fused image. Despite this, recent studies have revealed that fundamental perceptual processes are influenced by extremely brief temporal offsets in stimulus presentation. Some researchers have suggested that this is due to the action of a cortical temporal-binding mechanism, which would serve to keep multiple mental representations of one object distinct from those of other objects. There is now gathering evidence that these studies should be reassessed. This article describes evidence for sensitivity to fixational eye and head movements, which provides a purely spatial explanation for the earlier results. Taken in conjunction with other studies, the work serves to undermine the current body of behavioral evidence for a temporal-binding mechanism.

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In this paper we present a Gentzen system for reasoning with contrary-to-duty obligations. The intuition behind the system is that a contrary-to-duty is a special kind of normative exception. The logical machinery to formalise this idea is taken from substructural logics and it is based on the definition of a new non-classical connective capturing the notion of reparational obligation. Then the system is tested against well-known contrary-to-duty paradoxes.

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Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calculus. We extend their work to reasoning about probabilistic loops in the probabilistic refinement calculus. We apply our algebraic reasoning to derive transformation rules for probabilistic action systems. In particular we focus on developing data refinement rules for probabilistic action systems. Our extension is interesting since some well known transformation rules that are applicable to standard programs are not applicable to probabilistic ones: we identify some of these important differences and we develop alternative rules where possible. In particular, our probabilistic action system data refinement rules are new.

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In real-time programming a timeout mechanism allows exceptional behaviour, such as a lack of response, to be handled effectively, while not overly affecting the programming for the normal case. For. example, in a pump controller if the water level has gone below the minimum level and the pump is on and hence pumping in more water, then the water level should rise above the minimum level within a specified time. If not, there is a fault in the system and it should be shut down and an alarm raised. Such a situation can be handled by normal case code that determines when the level has risen above the minimum, plus a timeout case handling the situation when the specified time to reach the minimum has passed. In this paper we introduce a timeout mechanism, give it a formal definition in terms of more basic real-time commands, develop a refinement law for introducing a timeout clause to implement a specification, and give an example of using the law to introduce a timeout. The framework used is a machine-independent real-time programming language, which makes use of a deadline command to represent timing constraints in a machine-independent fashion. This allows a more abstract approach to handling timeouts.

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We propose a method for the timing analysis of concurrent real-time programs with hard deadlines. We divide the analysis into a machine-independent and a machine-dependent task. The latter takes into account the execution times of the program on a particular machine. Therefore, our goal is to make the machine-dependent phase of the analysis as simple as possible. We succeed in the sense that the machine-dependent phase remains the same as in the analysis of sequential programs. We shift the complexity introduced by concurrency completely to the machine-independent phase.