让智能空间的AI根据用户意图自动调节决策，平衡速度与精度。
UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces
- 用用户意图作为控制信号，动态调整任务优先级和资源分配。
- 在边缘设备上实现低延迟、高准确率的实时决策，兼顾计算成本。
- 适合需要快速响应且资源有限的智能环境应用，如智能家居、工业监控。
代理式人工智能（Agentic AI）正重塑智能体与决策支持系统，推动智能环境向更高效率、更优资源配置和更强韧性演进。本文提出UserCentrix——一种面向智能空间的混合代理编排框架，通过基于紧迫性和意图驱动的决策机制，优化资源管理并提升用户体验。该框架集成具备自主决策能力的交互模块，能动态平衡延迟、准确率与计算开销。用户意图作为核心控制信号，决定任务优先级、执行节奏与资源分配，并引导策略自适应调整以权衡速度与精度。实验表明，该框架可自主实现高效意图处理与实时监控，在资源受限的边缘条件下仍能保持推理质量与计算效率的平衡。
原文摘要 · Abstract (English)
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 autonomously enables efficient intent processing and real-time monitoring, while balancing reasoning quality and computational efficiency, particularly under resource-constrained edge conditions.
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