This article proposes a metamodel for describing the architecture of a High Level Architecture (HLA) compliant federation. A salient feature of the Federation Architecture Metamodel (FAMM) is the behavioral description of federates based on live sequence charts. FAMM formalizes the standard HLA Object Model and Federate Interface Specification. FAMM supports processing through automated tools, and in particular through code generation. It is formulated in metaGME, the metamodel for the Generic Modeling Environment. ACM Reference Format:Topçu, O., Adak, M., and Oǧuztüzün, H. 2008. A Metamodel for federation architectures. ACM Trans. Model.

Scenario development starts with capturing scenarios from the users and leads to the design and the development of the simulation environment to execute these scenarios. This paper proposes a scenario development process adopting a Model-Driven Engineering (MDE) perspective. It takes scenario development and the use of scenarios in simulation environment development put forth in IEEE Recommended Practice for Distributed Simulation Engineering and Execution Process (DSEEP) as a starting point. It then constructs a basic vocabulary including the definitions of operational, conceptual, and executable scenarios. Following MDE principles, scenario development is viewed as a series of model transformations. Operational scenarios, mostly defined in a natural language, are first transformed into conceptual scenarios, which conform to a formal metamodel. Then conceptual scenarios can be transformed into executable scenarios specified using a specific scenario definition language. Furthermore, it is also possible to generate the constructs of simulation environment design and development using model transformations. In this regard, a conceptual scenario metamodel is proposed adopting the Base Object Model metamodel as an example. Then this metamodel is used to present the proposed process with a sample operational scenario and conceptual scenario excerpts. Samples are shown how model transformation can be employed for developing a Federation Object Model and an executable scenario file.

In the context of adaptive and autonomous decision making, a computational model is needed to formalize and implement a practical goal deliberation mechanism that determines how goals can be evaluated, adopted, or rejected. Such a model is expected to lead to self-explanatory decision making, which is essential for understanding and influencing the behavior of autonomous agents and to pave the way to generate desirable macro-level behavior in self-adaptive, self-organizing systems. This article introduces an adaptive decision making architecture for agent-based simulation by promoting deliberative coherence and its extensions for decision making under uncertainty. To this end, a deliberative coherence-driven agent model is presented, and then is extended with run-time monitoring mechanisms. The architecture enables us to evaluate goals and competing tasks to facilitate the selection of the most coherent tasks with respect to a given goal, whereas the successful completion of those tasks contributes to the achievement of mission objectives for systems in shifting, ill-defined, and uncertain environments.

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