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    ABSTRACT: A human magician blends science, psychology, and performance to create a magical effect. In this paper we explore what can be achieved when that human intelligence is replaced or assisted by machine intelligence. Magical effects are all in some form based on hidden mathematical, scientific, or psychological principles; often the parameters controlling these underpinning techniques are hard for a magician to blend to maximize the magical effect required. The complexity is often caused by interacting and often conflicting physical and psychological constraints that need to be optimally balanced. Normally this tuning is done by trial and error, combined with human intuitions. Here we focus on applying Artificial Intelligence methods to the creation and optimization of magic tricks exploiting mathematical principles. We use experimentally derived data about particular perceptual and cognitive features, combined with a model of the underlying mathematical process to provide a psychologically valid metric to allow optimization of magical impact. In the paper we introduce our optimization methodology and describe how it can be flexibly applied to a range of different types of mathematics based tricks. We also provide two case studies as exemplars of the methodology at work: a magical jigsaw, and a mind reading card trick effect. We evaluate each trick created through testing in laboratory and public performances, and further demonstrate the real world efficacy of our approach for professional performers through sales of the tricks in a reputable magic shop in London.
    Full-text · Article · Nov 2014 · Frontiers in Psychology
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    ABSTRACT: We show how two iterated products of selection functions can both be used in conjunction with system T to interpret, via the dialectica interpretation and modified realizability, full classical analysis. We also show that one iterated product is equivalent over system T to Spector's bar recursion, whereas the other is T-equivalent to modified bar recursion. Modified bar recursion itself is shown to arise directly from the iteration of a different binary product of "skewed" selection functions. Iterations of the dependent binary products are also considered but in all cases are shown to be T-equivalent to the iteration of the simple products.
    Full-text · Article · Jul 2014 · Journal of Symbolic Logic
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    ABSTRACT: The energy consumption of the Internet accounts for approximately 1% of the world's total electricity usage, which may become one of the main constraints on its further growth. In response, we propose an evolutionary based dynamic energy management framework that reduces the overall energy consumption without degrading network performance. The main concept is to combine infrastructure sleeping with virtual router migration. During off-peak hours, the virtual routers are moved onto fewer physical platforms and the unused resources are placed in a sleep state to save energy. The sleeping physical platforms are then reawakened during busy periods. In particular, an evolutionary based algorithm called MOEA_VRM is developed to determine where to move the virtual routers in question. The algorithm is then evaluated using a multi-layer fluid flow event-driven simulator to assess its potential.
    No preview · Article · Jun 2014 · Sustainable Computing: Informatics and Systems
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