システム共同設計における分布的不確実性と適応的意思決定
Distributional Uncertainty and Adaptive Decision-Making in System Co-design
本論文は、複雑なシステム設計における不確実性を分布としてモデル化し、適応的な意思決定を可能にするco-designフレームワークの拡張を提案している。
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著者: Yujun Huang, Gioele Zardini
分類: math.OC, cs.RO, cs.SY, eess.SY
原文アブストラクト
Complex engineered systems require coordinated design choices across heterogeneous components under conflicting objectives and uncertain specifications. Monotone co-design provides a compositional framework for such problems. Performance of each subsystem is modeled with a design problem: a relation specifying what resources suffice to provide each functionality. Existing uncertain co-design models rely on interval bounds, which support worst-case reasoning but cannot represent probabilistic risk or multi-stage adaptive decisions. We develop a distributional extension of co-design that models uncertain design outcomes as distributions over design problems and supports adaptive decision processes through Markov-kernel re-parameterizations. Using quasi-measurable and quasi-universal spaces, we show that the standard co-design compositions remain compositional under this richer uncertainty, and introduce queries and observations extracting probabilistic trade-offs, including feasibility probabilities, confidence bounds, and distributions of minimal required resources. A task-driven unmanned aerial vehicle case study shows how the framework captures risk-sensitive and information-dependent design choices that interval models cannot express.
