
This work introduces a fundamental engineering law governing action under uncertainty in complex engineered systems.The law states that, in systems operating under uncertainty, the influence (authority) exerted on shared state must be proportionally bounded by what is justified at the moment the influence is applied. When justification is exhausted, control is no longer possible and system evolution becomes locked-in.The law applies to systems whose behavior is governed by process evolution, state transitions, timing, or dynamic coupling, and is independent of implementation, scale, or domain within its regime of applicability.This work is theoretical and structural in nature. It does not disclose implementation details, algorithms, software, hardware, or methods of enforcement. Supporting empirical validation and applied embodiments are intentionally excluded and may be subject to separate intellectual property protection.The purpose of this publication is to establish priority and formal definition of the law, clarify its applicability boundaries, and enable correct interpretation without enabling replication.
Engineering law, action under uncertainty, Constraint-based systems
Engineering law, action under uncertainty, Constraint-based systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
