Neuro-symbolic artificial intelligence: The state of the art
Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …
hitherto distinct approaches.” Neuro” refers to the artificial neural networks prominent in …
Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation 1
The study and understanding of human behaviour is relevant to computer science, artificial
intelligence, neural computation, cognitive science, philosophy, psychology, and several …
intelligence, neural computation, cognitive science, philosophy, psychology, and several …
The necessity of connection structures in neural models of variable binding
F van der Velde, M de Kamps - Cognitive neurodynamics, 2015 - Springer
In his review of neural binding problems, Feldman (Cogn Neurodyn 7: 1–11, 2013)
addressed two types of models as solutions of (novel) variable binding. The one type uses …
addressed two types of models as solutions of (novel) variable binding. The one type uses …
An indexing theory for working memory based on fast hebbian plasticity
Working memory (WM) is a key component of human memory and cognition. Computational
models have been used to study the underlying neural mechanisms, but neglected the …
models have been used to study the underlying neural mechanisms, but neglected the …
Neuro-symbolic artificial intelligence: application for control the quality of product labeling
The paper presents the implementation of an intelligent decision support system (IDSS) to
solve a real manufacturing problem at JSC “Savushkin Product”. The proposed system is …
solve a real manufacturing problem at JSC “Savushkin Product”. The proposed system is …
Designing a neural network primitive for conditional structural transformations
A Demidovskij, E Babkin - … 18th Russian Conference, RCAI 2020, Moscow …, 2020 - Springer
Among the problems of neural network design the challenge of explicit representing
conditional structural manipulations on a sub-symbolic level plays a critical role. In response …
conditional structural manipulations on a sub-symbolic level plays a critical role. In response …
[PDF][PDF] Q-SATyrus: Mapping Neuro-symbolic Reasoning into an Adiabatic Quantum Computer.
PMV Lima - NeSy, 2017 - ceur-ws.org
Much has been promised about quantum computing accelerators, but few actual commercial
technologies have been made available so far. The D-Wave Computers Series constitutes …
technologies have been made available so far. The D-Wave Computers Series constitutes …
[PDF][PDF] Neural relational learning through semi-propositionalization of bottom clauses
MVM França, G Zaverucha, ASA Garcez - 2015 AAAI Spring …, 2015 - cdn.aaai.org
Relational learning can be described as the task of learning first-order logic rules from
examples. It has enabled a number of new machine learning applications, eg graph mining …
examples. It has enabled a number of new machine learning applications, eg graph mining …
[PDF][PDF] The Boltzmann Machine: A Connectionist Model for Supra-Classical Logic
GC Blanchette - 2018 - ourarchive.otago.ac.nz
This thesis moves towards reconciliation of two of the major paradigms of artificial
intelligence: by exploring the representation of symbolic logic in an artificial neural network …
intelligence: by exploring the representation of symbolic logic in an artificial neural network …