A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies

Learning of Human-like Algebraic Reasoning Using Deep Feedforward Neural Networks

There is a wide gap between symbolic reasoning and deep learning. In this research, we explore the possibility of using deep learning to improve symbolic reasoning. Briefly, in a reasoning system, a deep feedforward neural network is used to guide rewriting processes after learning from algebraic reasoning examples produced by humans. To enable the neural network to recognise patterns of algebr...

Relational Knowledge Extraction from Neural Networks

The effective integration of learning and reasoning is a well-known and challenging area of research within artificial intelligence. Neural-symbolic systems seek to integrate learning and reasoning by combining neural networks and symbolic knowledge representation. In this paper, a novel methodology is proposed for the extraction of relational knowledge from neural networks which are trainable ...

?? Esprit Project 9119 Mix Modular Integration of Connectionist and Symbolic Processing in Knowledge-based Systems a Common Architecture for Integrating Case-based Reasoning and Neural Networks

انتخاب ناحیه‌های کاندید در سیستم‌های تشخیص و شناسایی اشیاء

According to the studies carried out in recent years, determination of the regional proposal is one of the crucial steps in detection and recognition of the objects included in an image. In fact, determination of this region has been like a bottleneck, gaining a significant computational energy. As a result, selection of suitable and fast approaches, under these circumstance, may enhance the pe...

On Common Ground: Neural-Symbolic Integration and Lifelong Machine Learning

Research efforts in Neural-Symbolic Integration and Lifelong Machine Learning have taken place with limited interactions over the last 20 years. These two areas of artificial intelligence share common ground and yet have much to learn from each other. This paper provides background, particularly on Lifelong Machine Learning, and presents a number of common areas of investigation with Neural-Sym...