This research opens up for consideration the topic of a generalized simulation Applications Programming Interface. Discussion evolves around representation of one phenomenon essential to such an Interface, which is the widely used Line-of-Sight methodology. The research describes an initial set of line of sight (LOS) attributes necessary for a generalized Applications Programming Interface. Determination of LOS is necessary for entity-based simulation of Army land operations. Attributes necessary for the determination of LOS are identified along with alternative implementation techniques. Capabilities and limitations of the alternative techniques and algorithms are described.

Recognizing the intention of others in real-time is a critical aspect of many human tasks. This article describes a technique for interpreting the near-term intention of an agent performing a task in real-time by inferring the behavioral context of the observed agent. Equally significantly, the knowledge used in this approach can be captured semi-automatically through observation of an agent performing tasks on a simulator in the context to be recognized. A hierarchical, template-based reasoning technique is used as the basis for intention recognition, where there is a one-to-one correspondence between templates and behavioral contexts or sub-contexts. In this approach, the total weight associated with each template is critical to the correct selection of a template that identifies the agent's current intention. A template's total weight is based on the contributions of individual weighted attributes describing the agent's state and its surrounding environment. The investigation described develops and implements a novel means of learning these weight assignments by observing actual human performance. It accomplishes this using back-propagation neural networks and fuzzy sets. This permits early discrimination between different pre-categorized behavioral contexts/sub-contexts on the human-controlled agent such as a military or passenger vehicle. We describe an application of this concept and the experimentation to determine the viability of this approach.2

It is widely accepted that acquisition of the knowledge behind military tactics has been one limiting factor in the development of computer generated forces (CGF) for training simulations. This has been addressed by several researchers with varying degrees of success. A system capable of building a knowledge base directly from a dialogue with a subject-matter expert (SME) could significantly reduce the human effort involved in capturing the knowledge and representing it directly in the modeling language. Because of its highly modular and hierarchical nature, the context-based reasoning (CxBR) modeling paradigm lends itself very well to facilitating the knowledge acquisition process for tactical behaviors. This paper describes an investigation into using CxBR as the foundation for a system that creates a (partial) model of tactical behavior through an interactive process with an SME. Through a sequence of queries from the system, the SME is progressively asked to provide details about the contexts that compose the context-based model of the expert's tactical know-how. A prototype was built and evaluated. A comparison to the effort taken to manually develop a knowledge base is reported. We use the simulation of a non-trivial maritime military confrontation as the benchmark for the comparisons.

Acoustics is an important consideration for realistic agent behavior in land combat, entity-based simulation models. This research describes basic approaches to representing and applying outdoor sound with limited discussion of the evolving field of indoor acoustics in such simulations. Attributes necessary for acoustics representations are identified within a framework along with alternative implementation techniques. Capabilities and limitations of selected alternative techniques and algorithms are described.

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Infornation , 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)2 Many of the newer simulation systems are using hierarchies for representing simulations where simulation specific primitive behaviors are combined in a temporal framework to compose complex behaviors.The use of these composite behaviors, describing and relating the primitive behaviors in a formal ontology, results in sophisticated behavior representations and promotes reuse of behaviors, as they are themselves independent of the simulation implementation.This research project developed OWL ontologies for describing both primitive behavior metadata and composite behaviors and a prototype within the OneSAF Objective System (OOS) simulation demonstrating how they could be used for composing standardized behaviors in the future. DRC developed a prototype behavior composer tool within the OOS simulation using the existing OOS graphical behavior composer tool. It was modified to allow transforming the XML behaviors created using the tool from the native OOS XML format into an RDF/XML format committed to the developed OWL behavior ontologies. SUBJECT TERMSThe transformation was accomplished using Extensible Stylesheet Language Transformation (XSLT) files embedded within the prototype. The prototype tool also allowed the user to add metadata to the RDF/XML composed behavior instances that use already known/memorized. With the filtering based on instance data conforming to the ontologies, the captured RDF/XML instance data allowed the user to reduce the search space to only the behaviors that might be applicable, a much more manageable set.The XSLT files for the o ntologies were then used with the 166 OOS Build 15 behaviors formatted in XML to create instance files of those behaviors in RDF/XML formats compatible with the ontologies. They were then validated to confirm that they conformed to the ontologies.For the JSAF option that was exercised, a couple of the behaviors from the vmovetask.fsm file were hand-coded, using the logic represented by the finite state machine (FSM) C-code, into RDF/XML instance files committed to the behavior ontologies. Those instance files were then validated to confirm that they conformed to the onto...