Logic programming has some drawbacks and limitations that make it computationally expensive, non-deterministic, and hard to debug. It requires a lot of memory and processing power to perform ...

The bees chose correctly between 63.6 and 72.1 per cent of the time give or take a few percentage points, suggesting a significant ability to quickly learn symbolic representations and their ...

The scope of Knowledge, Rationality and Action is interdisciplinary: it will be of interest to researchers in the fields of artificial intelligence, agents, computer science, knowledge representation, ...

The Journal of Logic, Language and Information explores the foundations of natural, formal, and programming languages, as well as the different forms of human and mechanized inference. It covers the ...

Hybrid deep neural-symbolic architecture for event-detection employs a deep neural network at the back-end to perform low-level reasoning and a symbolic logical module to perform high-level cognitive ...

The AI hype back then was all about the symbolic representation of knowledge and rules-based systems—what some nostalgically call "good old-fashioned AI" (GOFAI) or symbolic AI. It's hard to ...

In this paper, we propose a novel technique, Neuro-Symbolic Program Synthesis, to overcome the above-mentioned problems. Once trained, our approach can automatically construct computer programs in a ...