分散 发表于 2025-3-30 11:36:37
ral-Symbolic Learning Systems. .P is an example of such a system. In order to enable effective learning from examples and background knowledge, the main insight was to keep the network structure as simple as possible, and try to find the best symbolic representation for it. We have done so by presen问到了烧瓶 发表于 2025-3-30 16:09:10
http://reply.papertrans.cn/63/6261/626021/626021_52.png滔滔不绝的人 发表于 2025-3-30 16:38:42
http://reply.papertrans.cn/63/6261/626021/626021_53.pngInflamed 发表于 2025-3-30 22:30:56
David Li-Bland,Pavol Ševera these hybrid models, these methods use a knowledge compiler to turn the symbolic model into a differentiable arithmetic circuit, after which gradient descent can be performed. However, these methods require compiling a reasonably sized circuit, which is not always possible, as for many symbolic pro过分自信 发表于 2025-3-31 03:08:14
Ivan Contrerasmodels clearly capable of convincingly faking true reasoning behavior, the question of whether they are also capable of real reasoning—and how the difference should be defined—becomes increasingly vexed. Here we introduce a new tool, Logic Tensor Probes (LTP), that may help to shed light on the prob蛰伏 发表于 2025-3-31 07:45:33
antees. The challenge is how to effectively integrate neural and symbolic computation, to enable learning and reasoning from raw data. Existing pipelines that train the neural and symbolic components sequentially require extensive labelling, whereas end-to-end approaches are limited in terms of scal