Theoretical Foundations for Preference Representation in Systems Engineering

Abstract

The realization of large-scale complex engineered systems is contingent upon satisfaction of the preferences of the stakeholder. With numerous decisions being involved in all the aspects of the system lifecycle, from conception to disposal, it is critical to have an explicit and rigorous representation of stakeholder preferences to be communicated to key personnel in the organizational hierarchy. Past work on stakeholder preference representation and communication in systems engineering has been primarily requirement-driven. More recent value-based approaches still do not offer a rigorous framework on how to represent stakeholder preferences but assume that an overarching value function that can precisely capture stakeholder preferences exists. This article provides a formalism based on modal preference logic to aid in rigorous representation and communication of stakeholder preferences. Formal definitions for the different types of stakeholder preferences encountered in a systems engineering context are provided in addition to multiple theorems that improve the understanding of the relationship between stakeholder preferences and the solution space.

Requirements Rationalization and Synthesis Enabled by Model Synchronization

“…It should be noted that this paper does not attempt to define a strictly formal approach to requirements analysis (as advocated for example in [15][16][17]); rather, it uses a mathematical framework to assist the analyst within a joint cognitive paradigm [4]. Within the context of the broader research programme of the authors [18], we believe the joint cognitive paradigm begins to address in a pragmatic way calls for greater rigor in the development and application of Systems Engineering [19][20][21][22].…”

Formal reasoning of knowledge in systems engineering through epistemic modal logic

“…Similar to “ knows ” and “ believes ,” “ prefers ” is also a modal that has been dealt with in the fields of philosophy, 64–67 artificial intelligence, 68–70 and economics 71–73 . More recently, researchers in SE have proposed a formal logic system for preferences in SE, called modal preference logic that enables representation and reasoning of preferences 74 . The knowledge representation framework discussed in this paper can be combined with the modal preference logic to form a logic system that can handle the entanglement of preferences, knowledge, and beliefs, thereby resulting in a holistic framework for decision‐making in SE.…”

“…All of these workshops identified a need for underlying theoretical foundations in SE. Past researchers have proposed novel theoretical foundations for preference representation in SE using a logic‐based approach 74 . Since logic‐based approaches involve explicit mathematical representation of various elements in the domain of interest, it makes it comparatively compelling to use such approaches to derive mathematical insights about the relationships between the various elements in the domain, as compared to mathematical models that are more of a complicated blackbox.…”