Distributional Uncertainty and Adaptive Decision-Making in System Co-design

• URL: http://arxiv.org/abs/2603.14047v2
• Date: Thu, 19 Mar 2026 14:08:20 GMT
• Title: Distributional Uncertainty and Adaptive Decision-Making in System Co-design
• Abstract summary: Complex engineered systems require coordinated design choices across heterogeneous components.<n>Monotone co-design provides a compositional framework for such problems.<n>We develop a distributional extension of co-design that models uncertain design outcomes as over design problems.
• Score: 2.1221387541658476
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Complex engineered systems require coordinated design choices across heterogeneous components under multiple conflicting objectives and uncertain specifications. Monotone co-design provides a compositional framework for such problems by modeling each subsystem as a design problem: a feasible relation between provided functionalities and required resources in partially ordered sets. 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 interconnection operations remain compositional under this richer notion of uncertainty. We further introduce queries and observations that extract probabilistic design trade-offs, including feasibility probabilities, confidence bounds, and distributions of minimal required resources. A task-driven unmanned aerial vehicle case study illustrates how the framework captures risk-sensitive and information-dependent design choices that interval-based models cannot express.

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