Albinism
发表于 2025-3-26 22:19:13
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
竖琴
发表于 2025-3-27 03:14:23
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
Anticoagulant
发表于 2025-3-27 08:23:58
http://reply.papertrans.cn/47/4639/463888/463888_33.png
有害
发表于 2025-3-27 13:08:00
http://reply.papertrans.cn/47/4639/463888/463888_34.png
ITCH
发表于 2025-3-27 17:13:16
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
不可思议
发表于 2025-3-27 20:47:21
http://reply.papertrans.cn/47/4639/463888/463888_36.png
隐士
发表于 2025-3-28 00:57:55
http://reply.papertrans.cn/47/4639/463888/463888_37.png
售穴
发表于 2025-3-28 03:30:36
http://reply.papertrans.cn/47/4639/463888/463888_38.png
察觉
发表于 2025-3-28 09:25:45
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
decipher
发表于 2025-3-28 12:43:42
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