We present a novel architecture for an AI system that allows a priori knowledge to combine with deep learning. In traditional neural networks, all available data is pooled at the input layer. Our alternative neural network is constructed so that partial representations (invariants) are learned in the intermediate layers, which can then be combined with a priori knowledge or with other predictive analyses of the same data. This leads to smaller training datasets due to more efficient learning. In addition, because this architecture allows inclusion of a priori knowledge and interpretable predictive models, the interpretability of the entire system increases while the data can still be used in a black box neural network. Our system makes use of networks of neurons rather than single neurons to enable the representation of approximations (invariants) of the output.
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Rond 2022 koopt een vijfde van de wereldbevolking producten online over de grens. Consumenten krijgen steeds meer vertrouwen in buitenlandse aanbieders en Nederlandse webshops breiden uit naar grote buitenlandse e-commerce markten zoals in Duitsland.Samen met het Center for Market Insights, het onderzoekscentrum van Hogeschool van Amsterdam, onder leiding van Sjoukje Goldman en Alexander Lamprecht hebben Annabel Bak en Kristy Bruijn onderzoek gedaan naar de volgende onderzoeksvraag: Wat zijn de succes- en faalfactoren van Nederlandse webwinkeliers op de Duitse e-commerce markt?
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People tend to use the same door every time they enter and exit a building. When certainentrances are widely preferred over others, congestion can occur. This paper describes twointerventions to persuade visitors to use another entrance. The first intervention used sensory deprivation (darkness), and the second used guidance paths. The first intervention on sensory deprivation had the expected outcome. This intervention resulted in an avoidance of the darkened door. The second intervention had a result contrary to the expectations; it resulted in an increased preference for the door without guidance paths.
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