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The concept of a mission is important to system design and development, especially in system of systems (SoS) engineering. However, the diverse usage of the term 'mission' across disciplines often results in ambiguity regarding its role in practical applications in mission-centric engineering tasks. Clearly defined and precisely represented missions improve communication among stakeholders and help bridge interdisciplinary gaps. This study aims to investigate and analyze the state of the art for mission conceptualizations and representations and proposes a unified mission ontology (UMO) that improves semantic interoperability across various domains. To achieve this goal, we conducted a systematic literature review (SLR) to examine how missions are conceptualized and represented, analyzed the findings to obtain insight about cross-domain concepts related to missions, and developed a UMO that can be adapted to domain specific applications. The UMO facilitates semantic interoperability across domains through a high-level abstraction of shared concepts. To validate the comprehensiveness and adaptability of the UMO, we conducted coverage analysis using semantic similarity estimates to assess the equivalence of ontological concepts. This evaluation quantified the extent to which concepts from various domain-specific ontologies, including the mission engineering guideline, align with those in the UMO.

In its broadest sense, collaboration can be defined as a united effort to accomplish activities that ultimately lead to the achievement of shared objectives. This requires the sharing of information, planning, risks, and rewards between collaborating entities to a certain extent. In the case of systems of systems (SoS) where diverse and autonomous constituent systems (CS) interact to achieve shared goals, collaboration presents multifaceted challenges resulting from its distinct characteristics, including interconnectedness among the CS, heterogeneity, scalability concerns, dynamic environments, emergent behavior, stakeholder alignment challenges, and intricate decision-making processes. In order to enhance the achievement of the SoS goals, we propose a policy-guided collaboration approach. In this regard, we establish a learning-based policy generation process with the goal of guiding the decision-making behavior of CS. The practicality of the proposed approach is illustrated through a focused analysis of a high-rise building fire incident response system. Based on simulation results, the proposed approach performs better than the conventional approach in terms of SoS specific task completion time, performance with changes in simulation inputs, and efficiency. We also conducted a sensitivity analysis of task completion time by varying independent decision variables such as the number of CS instances and the size of collaborative tasks.