Titlebook: Inductive Logic Programming; 29th International C Dimitar Kazakov,Can Erten Conference proceedings 2020 Springer Nature Switzerland AG 2020

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Towards an ILP Application in Machine Ethics,In this paper we address the problem of representing and acquiring rules of codes of ethics in the online customer service domain. The proposed solution approach relies on the non-monotonic features of Answer Set Programming (ASP) and applies ILP. The approach is illustrated by means of examples tak

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On the Relation Between Loss Functions and T-Norms,his success has been the development of new loss functions, like the popular cross-entropy loss, which has been shown to provide faster convergence and to reduce the vanishing gradient problem in very deep structures. While the cross-entropy loss is usually justified from a probabilistic perspective

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Learning Logic Programs from Noisy State Transition Data, before being able to produce useful output. Such short-coming often limits their application to real world data. On the other hand, neural networks are generally known to be robust against noisy data. However, a fully trained neural network does not provide easily understandable rules that can be u

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Learning Probabilistic Logic Programs over Continuous Data,m in the field is probabilistic logic programming (PLP): the enabling of stochastic primitives in logic programming. While many systems offer inference capabilities, the more significant challenge is that of learning meaningful and interpretable symbolic representations from data. In that regard, in

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its environment it is necessary to be able to react to unforeseen events in real-time on basically all levels of abstraction. Having this goal in mind, our contributions reach from fundamental understanding of human injury due to robot-human collisions as the underlying metric for “safe” behavior, v