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Evidence record 557 · automatically gathered

Adaptive Utility driven Resource Orchestration for Resilient AI (AURORA-AI)

Modern AI systems are increasingly deployed under non-stationary computational, demographic, and operational conditions in which static resource allocation strategies degrade both predictive performance and human-centric properties such as fairness and explainability. This paper presents AURORA-AI, an Adaptive Utility-driven Resource Orchestration framework for Resilient AI that unifies Hamilton-Jacobi-Bellman feedback control, Lyapunov-based stability monitoring, and a fairness-aware composite

Record details

Published: 25 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (25 June 2026), “Adaptive Utility driven Resource Orchestration for Resilient AI (AURORA-AI),” evidence record 557, https://ethics.ai/record/557 (originally published by arXiv).

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