Beyond Traditional Neural Networks: Toward adding Reasoning and Learning Capabilities through Computational Logic Techniques
Artificial Intelligence
2023-08-31 v1 Machine Learning
Logic in Computer Science
Multiagent Systems
Abstract
Deep Learning (DL) models have become popular for solving complex problems, but they have limitations such as the need for high-quality training data, lack of transparency, and robustness issues. Neuro-Symbolic AI has emerged as a promising approach combining the strengths of neural networks and symbolic reasoning. Symbolic knowledge injection (SKI) techniques are a popular method to incorporate symbolic knowledge into sub-symbolic systems. This work proposes solutions to improve the knowledge injection process and integrate elements of ML and logic into multi-agent systems (MAS).
Cite
@article{arxiv.2308.15899,
title = {Beyond Traditional Neural Networks: Toward adding Reasoning and Learning Capabilities through Computational Logic Techniques},
author = {Andrea Rafanelli},
journal= {arXiv preprint arXiv:2308.15899},
year = {2023}
}
Comments
In Proceedings ICLP 2023, arXiv:2308.14898