Verfahren zur Automatischen Wissensverfeinerung und Aufgabenausführung

Details

Veröffentlichungs-Nr.

EP4787246

Anmeldetag

12. Dezember 2025

Veröffentlichung

5. August 2026

Rechtsraum

EP

IPC

G06N5/022, G06N20/00

Abstract

This disclosure relates generally to a method for automatic knowledge refinement and task execution in robotic agents using a domain-agnostic knowledge base. Conventional Large Language Model (LLM) based methods break down complex tasks into sub-tasks but may generate incorrect steps or refer to unavailable objects or actions. While the robotic agents leverages prior-domain specific-knowledge, the unavailability of such structured knowledge in many practical domains and difficulty in updating data reliably makes agent-based task execution problematic. The integration of the domain-agnostic knowledge base with a Multi-modal Language Models (MLM) or LLM enables the robotic agent to perform tasks that span multiple domains without the constraints imposed by traditional, domain-specific knowledge bases. Combining the domain-agnostic knowledge base and the MLM allows for the generation of refined action sequences that are adaptable to the nuances of complex tasks, thereby enhancing the robotic agent's operational versatility and effectiveness.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete