Tractable Boolean and Arithmetic Circuits
Abstract
Tractable Boolean and arithmetic circuits have been studied extensively in AI for over two decades now. These circuits were initially proposed as "compiled objects," meant to facilitate logical and probabilistic reasoning, as they permit various types of inference to be performed in linear-time and a feed-forward fashion like neural networks. In more recent years, the role of tractable circuits has significantly expanded as they became a computational and semantical backbone for some approaches that aim to integrate knowledge, reasoning and learning. In this article, we review the foundations of tractable circuits and some associated milestones, while focusing on their core properties and techniques that make them particularly useful for the broad aims of neuro-symbolic AI.
Cite
@article{arxiv.2202.02942,
title = {Tractable Boolean and Arithmetic Circuits},
author = {Adnan Darwiche},
journal= {arXiv preprint arXiv:2202.02942},
year = {2022}
}
Comments
An earlier version of this article appeared in the following edited book. Pascal Hitzler and Md Kamruzzaman Sarker, editors. Neuro-Symbolic Artificial Intelligence: The State of the Art, volume 342 of Frontiers in Artificial Intelligence and Applications. IOS Press, 2021