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Model reuse is a longstanding challenge within the defense simulation modeling community. While other disciplines successfully apply component-based approach to build systems, this approach has proven difficult to apply in simulation model development. The significance of employing explicit and distinct experimental frames to support reuse is already well recognized. Yet, characterization of the original context of a model is one of the least appreciated aspects and central to reuse and composability. Methods and tools are needed to provide mechanisms for structured representation and storage of context information, effective ways for retrieving it, and the possibility to relate it to the developer's intention. To this end, the basic model-simulator-experimental frame viewpoint is revisited to assert the role of context in reuse. The significance of separating concept, content, context, and simulator is discussed under the discrete-event system specification (DEVS) framework to provide a basis and rationale for contextualized simulation models. An abstract design strategy is presented to facilitate packaging and distribution of concept and context specification objects along with simulation models to improve reuse and composability.

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Modeling & Simulation (M&S) is making successful contributions to different areas in industry and academia. However, there are certain key issues that are preventing the field from addressing larger domains and from achieving wide-scale impact. Formulating these as grand challenges arguably focuses attention on these key issues and may bring a critical mass of effort to bear that could result in a major leap forward. This article is one of several concurrent activities aimed at reinvigorating the debate on grand challenges in M&S. These grand challenges include Big Simulation, human behavior, composability, cloud-based M&S, reproducibility in M&S research and the democratization of M&S. Two themes emerge: the need for large-scale cloud-based cyberinfrastructures for M&S and the democratized access to M&S and its outputs.

The use of simulation modeling in computational analysis of organizations is becoming a prominent approach in social science research. However, relying on simulations to gain intuition about social phenomena has significant implications. While simulations may give rise to interesting macro-level phenomena, and sometimes even mimic empirical data, the underlying micro and macro level processes may be far from realistic. Yet, this realism may be important to infer results that are relevant to existing theories of social systems and to policy making. Therefore, it is important to assess not only predictive capability but also explanation accuracy of formal models in terms of the degree of realism reflected by the embedded processes. This paper presents a process-centric perspective for the validation and verification (V&V) of agent-based computational organization models. Following an overview of the role of V&V within the life cycle of a simulation study, emergent issues in agent-based organization model V&V are outlined. The notion of social contract that facilitates capturing micro level processes among agents is introduced to enable reasoning about the integrity and consistency of agent-based organization designs. Social contracts are shown to enable modular compositional verification of interaction dynamics among peer agents. Two types of consistency are introduced: horizontal and vertical consistency. It is argued that such local consistency analysis is necessary, but insufficient to validate emergent macro processes within multi-agent organizations. As such, new formal validation metrics are introduced to substantiate the operational validity of emergent macro-level behavior.