The idea of integrating symbolic and sub-symbolic approaches to make intelligent systems (IS) understandable and explainable is at the core of new fields such as neuro-symbolic computing (NSC). This work lays under the umbrella of NSC, and aims at a twofold objective. First, we present a set of guidelines aimed at building explainable IS, which leverage on logic induction and constraints to integrate symbolic and sub-symbolic approaches. Then, we reify the proposed guidelines into a case study to show their effectiveness and potential, presenting a prototype built on the top of some NSC technologies
Neural-Symbolic approaches are becoming increasingly prominent due to their ability to integrate kno...
Despite the recent remarkable advances in deep learning, we are still far from building machines wit...
International audienceWe discuss a perspective aimed at making black box models more eXplainable, wi...
The idea of integrating symbolic and sub-symbolic approaches to make intelligent systems (IS) unders...
We discuss the purpose of neural-symbolic integration including its principles, mechanisms and appli...
partially_open3noSpecial Issue for the Twentieth Edition of the Workshop ‘From Objects to Agents’ ...
Current advances in Artificial Intelligence and machine learning in general, and deep learning in pa...
We discuss the purpose of neural-symbolic integration including its principles, mechanisms and appli...
The need for neural-symbolic integration becomes apparent as more complex problems are tackled, and ...
We investigate the potential of Neural-Symbolic integration to reason about what a neural network ha...
In the era of digital revolution, individual lives are going to cross and interconnect ubiquitous on...
Neuro-Symbolic Integration is an interdisciplinary area that endeavours to unify neural networks and...
Humans interact with the environment using a combination of perception - transforming sensory inputs...
There is an obvious tension between symbolic and subsymbolic theories, because both show complementa...
The construction of computational cognitive models integrating the connectionist and symbolic para...
Neural-Symbolic approaches are becoming increasingly prominent due to their ability to integrate kno...
Despite the recent remarkable advances in deep learning, we are still far from building machines wit...
International audienceWe discuss a perspective aimed at making black box models more eXplainable, wi...
The idea of integrating symbolic and sub-symbolic approaches to make intelligent systems (IS) unders...
We discuss the purpose of neural-symbolic integration including its principles, mechanisms and appli...
partially_open3noSpecial Issue for the Twentieth Edition of the Workshop ‘From Objects to Agents’ ...
Current advances in Artificial Intelligence and machine learning in general, and deep learning in pa...
We discuss the purpose of neural-symbolic integration including its principles, mechanisms and appli...
The need for neural-symbolic integration becomes apparent as more complex problems are tackled, and ...
We investigate the potential of Neural-Symbolic integration to reason about what a neural network ha...
In the era of digital revolution, individual lives are going to cross and interconnect ubiquitous on...
Neuro-Symbolic Integration is an interdisciplinary area that endeavours to unify neural networks and...
Humans interact with the environment using a combination of perception - transforming sensory inputs...
There is an obvious tension between symbolic and subsymbolic theories, because both show complementa...
The construction of computational cognitive models integrating the connectionist and symbolic para...
Neural-Symbolic approaches are becoming increasingly prominent due to their ability to integrate kno...
Despite the recent remarkable advances in deep learning, we are still far from building machines wit...
International audienceWe discuss a perspective aimed at making black box models more eXplainable, wi...