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simulation semantics. Including xNA as a component of the prototype SWS deployed in UR2015 extends
the Service Orientated Architecture (SOA) approach to provide a semantics-based integration of analyst
knowledge, stored in a repository named Operational Net Assessment (ONA), with emergent simulation
data. xNA supports multi-granularity and multi-disciplinary data to facilitate integration in the context of a
diversity of models and data sources. xNA can also receive incremental data updates from analysts and
automated data collection tools. More details on the prototype SWS are given in “JFCOM J9 Deployment
of SWS 0.5” below.

Model Development IDEs
SWS provides a set of tools based on the ontological repository for use by experts from various domains to
develop and experiment with models in the synthetic environment. A researcher begins with a set of
theories to test. Using algorithms of how the theories interact with the rest of the synthetic world, the
researcher creates models. The researcher designs a complete experiment environment using the new
models and leveraging existing models by creating a profile consisting of a selection of parameters from
the ontological data repository that fulfill the input requirements and support the experiment’s scenario.
SEAS Integrated Development Environment (SIDE) provides the tools to create and retrofit the artificial
agents in SEAS. Researchers will first design new types of agents along with the DNA and memory these
types of agents will have using the design interfaces of SIDE. The design interfaces also allow the DNA
and memory of existing agent types to be modified. After creating new agent types, SIDE is used to
configure the population makeup of the new agents in the synthetic environment.
After the creation of new agents, researchers use Just-in-time Modeling Environment (JIME) to create and
modify the behaviors of agents. Agent behaviors can be mathematical models based on variables that the
agents sense from the environment or can be described procedurally using a workflow engine, a
customizable system composed of states, transitions, and messages. The behaviors describe how agents
interact with their environment and other fellow agents.
Before incorporating the new agents into the reference world of SWS, agents are prudently tested in the
Bullpen tool. Using Bullpen, the behavior of agents is observed in a limited and controlled environment.
Researchers create profiles of environment variables for Bullpen experiments to observe the range of
decisions an agent makes and agent’s resulting actions.
Additionally, the modeling environment of SWS is extensible using ModelNet. ModelNet is a collection of
web-services that provides the functionalities of the aforementioned tools. Using the web-services, external
modeling tools can be integrated into the SWS to enable researchers to use modeling tools that are best for
their domain.

Excursion Management
SWS provides a configurable interface for configuring an excursion from the continuously running SWS
reference world to meet the individual needs of a user. User needs addressed by the Excursion Manager

Exploring multiple courses of action by taking different sets of actions in identical copies of the
reference world.

Using proprietary or classified data in a controlled experiment without interfering with the
publicly accessible SWS.

Constructing a synthetic environment for only a portion of the world or including only certain
models, simulations, tools, visualizations, or data sources.

Conducting simultaneous excursions in different areas of the world and merging the
nonproprietary and unclassified results together.

Once an excursion is configured, the Excursion Manager fulfills the following: