Neuro-Symbolic Reinforcement Learning with First-Order Logic 带有一阶逻辑的神经符号强化学习 emnlp 2021 论文地址:aclanthology.org/2021.e Abstract 深度强化学习(RL)方法在收敛之前往往需要多次试验,并且没有提供训练后的策略的直接可解释性。为了能在RL中实现快速收敛并且提供策略的可解释性,本文提出了一种基于文...
A computer-implemented method for reinforcement learning with Logical Neural Networks (LNNs) is provided including receiving a plurality of observation text sentences from a target environment, extracting one or more propositional logic values from the plurality of observation text sentences, finding a ...
Daiki Kimura, Masaki Ono, Subhajit Chaudhury, Ryosuke Kohita, Akifumi Wachi, Don Joven Agravante, Michiaki Tatsubori, Asim Munawar, and Alexander Gray, "Neuro-Symbolic Reinforcement Learning with First-Order Logic", EMNLP 2021. Details and bibtex ...
The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop AI systems with more human-like reasoning capabilities by combining symbolic reasoning with connectionist learning. We survey the literature on neuro-symbolic AI during the last two decades, including books...
最后,机器学习和知识表示和推理具有互补优势的领域是知识工程,包括知识库补全和数据驱动的本体学习(ontology learning)。在包括知识库补全和数据驱动的本体学习这个应用领域,丰富且大规模的符号表示已经与数据一起存在,包括可以与图神经网络等神经网络结合的知识图(Lamb et al. 2020;Carvalho)等人,2022)。就语言模型而言...
Neuro-Symbolic Reinforcement Learning: Logical Optimal Action (LOA), a novel RL with Logical Neural Network (LNN) on text-based games machine-learningreinforcement-learningartificial-intelligenceneuro-symbolicneuro-symbolic-ai UpdatedJul 6, 2023
成立时间:December 20, 2016 研究组 Deep Learning Group The Deep Learning group advances the state-of-the-art in deep learning to achieve general intelligence. We develop algorithms, models, and systems in deep supervised and unsupervised learning, deep reinforcement learning, and ne...
In this work, we present Neuro-Symbolic Predicates, a first-orderion language that combines the strengths of symbolic and neural knowledge representations. We outline an online algorithm for inventing such predicates and learningworld models. We compare our approach to hierarchical reinforcement learning...
select article Trails of meaning construction: Symbolic artifacts engage the social brain Research articleAbstract only Trails of meaning construction: Symbolic artifacts engage the social brain Kristian Tylén, Johanne Stege Philipsen, Andreas Roepstorff, Riccardo Fusaroli Pages 105-112 Article preview sel...
Neither deep neural networks nor symbolic artificial intelligence (AI) alone has approached the kind of intelligence expressed in humans. This is mainly because neural networks are not able to decompose joint representations to obtain distinct objects (t