Symbolic Logic, Inc., a research and development organization, focuses on developing proprietary algorithms that model and predict behaviour of dynamic systems. It is also developing a set of tools ...

Researchers at TU Wien have discovered an unexpected connection between two very different areas of artificial intelligence: Large Language Models (LLMs) can help solve logical problems—without ...

Abstract: This study examines the issue of interpretability in fault diagnosis for rolling bearings using a symbolic learning technique. We propose the adoption of weighted signal temporal logic (wSTL ...

Will computers ever match or surpass human-level intelligence — and, if so, how? When the Association for the Advancement of Artificial Intelligence (AAAI), based in Washington DC, asked its members ...

Abstract: Programmable Logic Controllers (PLC) are widely used in industry. The reliability of the PLC is vital to many critical applications. This paper presents a novel approach to the symbolic ...

As of , had a $0.0 market capitalization, putting it in the percentile of companies in the industry. does not have a meaningful P/E due to negative earnings over the last 12 trailing months. ’s ...

Logic Tensor Network (LTN) is a Neural-Symbolic (NeSy) framework which supports learning of neural networks using the satisfaction of a first-order logic knowledge base as an objective. In other words ...

Z3 is an efficient Satisfiability Modulo Theories (SMT) solver from Microsoft Research. Z3 is a solver for symbolic logic, a foundation for many software engineering tools. SMT solvers rely on a tight ...

Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s abilities, ...

MR. MCCOLL still expresses surprise at my declining to answer a Yes or No question which he was pleased to put to me in NATURE (vol. xxiv. p. 124). It was, I should think, almost unique in a ...