14 resultados para Configural reasoning

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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Like faces, body postures are susceptible to an inversion effect in untrained viewers. The inversion effect may be indicative of configural processing, but what kind of configural processing is used for the recognition of body postures must be specified. The information available in the body stimulus was manipulated. The presence and magnitude of inversion effects were compared for body parts, scrambled bodies, and body halves relative to whole bodies and to corresponding conditions for faces and houses. Results suggest that configural body posture recognition relies on the structural hierarchy of body parts, not the parts themselves or a complete template match. Configural recognition of body postures based on information about the structural hierarchy of parts defines an important point on the configural processing continuum, between recognition based on first-order spatial relations and recognition based on holistic undifferentiated template matching.

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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.