4 Neural-Symbolic Learning 4.1 Inductive Logic Programming 归纳逻辑程序设计(ILP)可以利用神经符号计算的学习能力,从实例中自动构造逻辑程序。ILP方法分为自底向上和自顶向下。 自底向上方法通过从示例中提取特定子句来构造逻辑程序。例如,构造cilp++时使用了底子句命题化技术。CRILP系统将clip++生成的底子句与rbm...
论文地址:Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks (aaai.org) Abstract 关于神经符号归纳逻辑编程的工作出现了有一定前景的方法,使它可以从嘈杂的真实世界数据中学习解释规则。有些人用模糊或实值逻辑的可微分算子来近似逻辑算子,但这些算子是没有参数的,这削弱了它们适应数据的能力。其...
A curated list of papers on Neural Symbolic and Probabilistic Logic. Papers are sorted by their uploaded dates in descending order. Each paper is with a descrip...
NeuroLISP: High-level symbolic programming with attractor neural networksGregory P. Davis aGarrett E. Katz bRodolphe J. Gentili cJames A. Reggia a
It is trained during dreaming sleep, and produces a contextual grammar for each task, which assigns a high probability to the correct solution (Section “Neurosymbolic programming with Dreamcoder”). The recognition model begins with a feature extractor module which converts a task to a fixed-...
probabilitylogic-programmingneural-module-networksneural-symbolicneurosymbolicdeep-logicneural-logicprobabilistic-logic UpdatedSep 5, 2023 AIKA (Artificial Intelligence for Knowledge Acquisition) is an innovative approach to neural network design, diverging from traditional architectures that rely heavily on rigid...
A Neural Lambda Calculus: Neurosymbolic AI meets the foundations of computing and functional programming 来自 Semantic Scholar 喜欢 0 阅读量: 3 作者:J Flach,LC Lamb 摘要: Over the last decades, deep neural networks based-models became the dominant paradigm in machine learning. Further, the use ...
Knowledge graph reasoning Knowledge graph embedding Symbolic reasoning Neural-symbolic reasoning 1. Introduction SYMBOLISM and connectionism are two main paradigms of Artificial Intelligence. Symbolism assumes the basic units which compose the human intelligence are symbols, and the cognitive process is a ser...
Parallel Distributed Genetic Programming (PDGP) is a new form of genetic programming suitable for the development of parallel programs in which symbolic and neural processing elements can be combined in a free and natural way. This paper describes the representation for programs and the genetic opera...
Sun R, Alexandre F (2013) Connectionist-symbolic integration: from unified to hybrid approaches Chaudhuri S, Ellis K, Polozov O, Singh R, Solar-Lezama A, Yue Y (2021) Neurosymbolic programming. Found Trends® Program Lang 7(3):158–243 ...