First Order Logic

First-order logic (FOL) is a formal system for representing knowledge and reasoning, aiming to provide a rigorous framework for automated deduction and knowledge representation. Current research focuses on extending FOL's capabilities, including integrating it with neural networks (e.g., using graph neural networks or decision trees to learn logical classifiers) and developing efficient algorithms for query answering and inference in complex scenarios, such as those involving large knowledge graphs or natural language processing. These advancements are improving the efficiency and applicability of FOL in diverse fields, from automated theorem proving and knowledge base querying to the interpretation of machine learning models and human-robot interaction.