2 Prolegomenon to Neural-Symbolic Computing 神经-符号计算结合了学习、推理和知识提取。神经符号系统是模块化的,并寻求具有组合性的特性。基于知识的人工神经网络(KBANN)、连接主义归纳学习和逻辑编程(CILP)系统是最有影响力的模型,它们结合了逻辑推理和神经学习。 KBANN系统是第一个允许在神经网络和知识提取中利用背...
A neural-symbolic computing engine can have two or more modules that are configured to cooperate with each other in order to create one or more gradient- based machine learning models that use machine learning on i) knowledge representations and ii) reasoning to solve an issue. A model ...
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective. 2020. IJCAI. 论文地址: https://www.ijcai.org/Proceedings/2020/679www.ijcai.org/Proceedings/2020/679 摘要:神经符号计算现在已经成为学术和工业研究实验室感兴趣的课题。图神经网络广泛应用于关系和符号领域,广泛应用于组合优...
Garcez Ad, Gori M, Lamb LC, Serafini L, Spranger M, Tran SN (2019) Neural-symbolic computing: an effective methodology for principled integration of machine learning and reasoning. arXiv preprintarXiv:1905.06088 De Raedt L, Dumančić S, Manhaeve R, Marra G (2020) From statistical relat...
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective IJCAI Paper A Survey on Neural-Symbolic with GNN. 2020 Symbolic, Distributed and Distributional Representations for Natural Language Processing in the Era of Deep Learning: a Survey Frontiers in Robotics and AI Paper In th...
A.d. Garcez, M. Gori, L.C. Lamb, L. Serafini, M. Spranger, S.N. Tran Neural-symbolic Computing: an Effective Methodology for Principled Integration of Machine Learning and Reasoning (2019) arXiv preprint arXiv:1905.06088 Google Scholar Gardner et al., 2013 M. Gardner, P.P. Taluk...
An ongoing research effort is described whose goal is to develop a single, unified computational paradigm for conjoint computing which integrates concepts from symbolic processing, numeric processing, and neural network technologies. The result will be a novel methodology for synthesizing intelligent systems...
Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid ...
Computer Science - Neural and Evolutionary ComputingResearch on integrated neural-symbolic systems has made significant progress in the recent past. In particular the understanding of ways to deal with symbolic knowledge within connectionist systems (also called artificial neural networks) has reached a ...
With the support of computer software and hardware for tensor computing and parallel computing of deep learning, the 𝑁𝑁𝑚𝑜𝑑𝑒𝑙NNmodel has higher computing efficiency and better scalability for large-scale ABox reasoning than 𝑂𝑛𝑡𝑜𝑟𝑒𝑎𝑠𝑜𝑛Ontoreason. The above...