Work

Adaptive and Scalable Knowledge Management for Robotic Applications via Logic Languages

Year: 2024

Type: conference-paper

Abstract: This work outlines a framework that combines knowledge representation systems with planning capabilities. It is based on four main pillars: Automated knowledge extraction from natural language descriptions using Large Language Models (LLMs). Generation of temporal plans for multi-robot systems using inference rules. Automatic translation of plans into executable formalisms. Runtime monitoring of the plan execution, learning from exceptions, and updating the knowledge-base dynamically.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14731119

Authors: Saccon, Enrico, Tikna, Ahmet, Lamon, Edoardo, Palopoli, Luigi, Roveri, Marco

Language: English

Topic: AI-based Problem Solving and Planning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6912058799

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