[2505.00472] UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces

Computer Science > Artificial Intelligence arXiv:2505.00472 (cs) [Submitted on 1 May 2025 (v1), last revised 6 Apr 2026 (this version, v2)] Title:UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces Authors:Alaa Saleh, Sasu Tarkoma, Praveen Kumar Donta, Anders Lindgren, Naser Hossein Motlagh, Schahram Dustdar, Susanna Pirttikangas, Lauri Lovén View a PDF of the paper titled UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces, by Alaa Saleh and 7 other authors View PDF Abstract:Agentic Artificial Intelligence (AI) constitutes a transformative paradigm in the evolution of intelligent agents and decision-support systems, redefining smart environments by enhancing operational efficiency, optimizing resource allocation, and strengthening systemic resilience. This paper presents UserCentrix, a hybrid agentic orchestration framework for smart spaces that optimizes resource management and enhances user experience through urgency-aware and intent-driven decision-making mechanisms. The framework integrates interactive modules equipped with agentic behavior and autonomous decision-making capabilities to dynamically balance latency, accuracy, and computational cost. User intent functions as a governing control signal that prioritizes decisions, regulates task execution and resource allocation, and guides the adaptation of decision-making strategies to balance trade-offs between speed and accuracy. Experimental results demonstrate that the framework...