Terms, Definitions and Acronyms

This page defines the acronyms that the content of this site uses and presents definitions for some of the terms it uses.


The table below defines the acronyms used in this website.

Definitions of the Acronyms Used on this Site
BGS Benefits Gateway Services
C2 command and control
C3 command, control and communications
C4I command, control, communications, computing and intelligence
CGF computer generated forces
DARPA Defense Advanced Research Projects Agency
DMSO Defense Modeling and Simulation Office
DNA Defense Nuclear Agency
DoD Department of Defense
FASS Fleet Aerial Support Simulation
GM General Motors Corporation
GSR Ground Surveillance Robot
HLA High Level Architecture
IEEE Institute of Electrical and Electronic Engineers
IR&D independent research and development
JECP Joint Expeditionary Collective Protection
JEM Joint Effects Model
JOEF Joint Operational Effects Federation
JSIMS Joint Simulation System
JWARN Joint Warning and Reporting Network
JWARS Joint Warfare Simulation
KBS knowledge-based system
NASA National Aeronautics and Space Administration
NATO North Atlantic Treaty Organization
NAVSEA Naval Sea Systems Command
NIST National Institute of Standards and Technology
NOSC Naval Ocean Systems Center
NWSS nuclear weapon site security
ONR Office of Naval Research
OR Oregon
PO Post Office
R&D research and development
RPG Recommended Practices Guide
SAFOR semi-automated forces
SERPENT Simulation Environment & Response Program Execution Nesting Tool
SIMNET Simulation Network
SISO Simulation Interoperability Standards Organization
SLOC source lines of code
SME subject matter expert
SPAWAR Space and Naval Systems Command
SPM System Performance Model
US United States of America
USMC US Marine Corps
V&V verification and validation
VBA Veterans Benefits Administration
VBMS Veterans Benefits Management System
VETSNET Veteran Service Network
VV&A verification, validation and accreditation

Terms and Definitions

The alphabetized list below provides largely authoritative definitions of some of the specialized terms used in this website. The numbers given in the reference citations of these definitions correspond with the reference numbers in the list of references given in the References section of this page.

1. The process of selecting the essential aspects of a simuland to be represented in a model or simulation while ignoring those aspects that are not relevant to the purpose of the model or simulation.
2. The set of elements produced by this process [1].
3. The act or process of separating the inherent qualities or properties of something from the actual physical object or concept to which they belong [2].
4. A product of this process, as a general idea or word representing a physical concept [2].
acceptability criteria
Criteria that a particular model, simulation or simulation federation must meet to be suitable for a specific purpose; accreditation criteria [3].
Official acceptance or certification that a model, simulation or federation of simulations and their associated data are suitable for a specific purpose or intended use [4, 5].
accreditation agent
The individual, group or organization designated by the accreditation authority to conduct an accreditation assessment of a model, simulation or simulation federation [3, 5]. See accreditation authority.
accreditation authority
The individual with the appropriate rank, grade, responsibility and authority to accredit a model, simulation or federation of simulations for a particular purpose or intended use [6, 7]. See accreditation agent.
accreditation criteria
A set of standards that a particular model, simulation or simulation federation must meet to be accredited for a specific purpose or intended use [3, 5]. See acceptability criteria.
The degree to which a set of parameters or variables within a model or simulation conform to some chosen standard or referent [4]. See resolution, fidelity, precision.
adaptive system
A system that can change its own function to accommodate to changes in its task, its surroundings or its resources. A type of reconfigurable system.
1. The ability to group items, whether entities or processes, while preserving the effects of item behavior and interaction while grouped [8].
2. A relationship between objects in the data model where one object contains other objects [9].
A prescribed set of well-defined, unambiguous rules or processes for solving a problem in a finite number of steps [10].
The structure of components in a program or system, their interrelationships, and the principles and guidelines governing their design and evolution over time [8].
1. A statement or proposition used in the premises of arguments and assumed as self-evidently true without proof [11].
2. A well formed formula that is stipulated rather than proved to be so through the application of rules of inference [12].
1. For a given object, how attribute value changes affect or are affected by the attribute value changes of the same or other objects [13].
2. The way in which a system responds to stimuli over time [4].
boundary condition
The values assumed by the variables in a system, model or simulation when one or more of them is at a limiting value at the edge of the domain of interest. See final condition, initial condition [14, 15].
1. Capable of being believed; plausible [2].
2. Deserving confidence [2].
3. The extent to which a user can correctly infer information from a model or simulation [3].
4. The relevance that the user sees and the confidence that the user has that a model or simulation can serve their purpose [3].
A description of a group of objects with similar properties, common behavior, common relationships or common semantics [16].
computer generated forces
A computer representation of battlefield participants that attempts to approximate human behavior sufficiently so that those forces will perform some actions automatically (i.e., without requiring human intervention); semi-automated forces [8].
1. A representation of facts, concepts or instructions in a formalized manner suitable for communication, interpretation or processing by humans or by automatic means [17-19].
2. Assumed, given, measured or otherwise determined facts or propositions used to draw a conclusion or make a decision [2].
A collection of interrelated data, often with controlled redundancy, organized according to a schema to serve one or more applications; the data are stored so that they can be used by different programs without concern for the data structure or organization. A common approach is used to add new data and to modify and retrieve existing data [17-19].
An individual, group or organization responsible for actually developing or modifying a system or subsystem in accordance with design requirements and specifications. A developer may use a model, simulation or simulation federation in the system development process [3].
Pertaining to a process, model, simulation or variable whose outcome, result, or value does not depend upon chance [15, 20]. See stochastic.
Pertaining to information that is derived from observation, experiment or experience [14, 15].
1. A distinguishable person, place, unit, thing, event or concept about which information is kept [21].
2. Something that exists as a particular and discrete unit [2].
equation of state
1. A relation, empirical or derived, between the properties describing the state of a substance or system [22].
2. The relationship between observables in a natural system [4]. See state, observable, input, output.
A condition in which all acting influences are canceled by others, resulting in a stable, balanced or unchanging system [2, 14]. See steady state.
The difference between an observed, measured or calculated value and a correct value [1].
error model
1. A model used to estimate or predict the extent of deviation of the behavior of an actual system from the desired behavior of the system. See error [14, 15].
2. In software evaluation, a model used to estimate or predict the number of remaining faults, required test time, and similar characteristics of a system [14, 15].
1. A change in an object attribute value, an interaction between objects, an instantiation of a new object, or a deletion of an existing object that is associated with a particular point on the simulated time axis [16].
2. An individual stimulus from one object to another at a particular point of time [4].
A system of interacting federates, a common Federation Object Model, and supporting infrastructure relying upon a common understanding of the simulated objects and used as a whole for some specific purpose [5, 7, 16].
1. The degree to which a model or simulation reproduces the state and behavior of a real world object or the perception of a real world object, feature, condition or chosen standard in a measurable or perceivable manner; a measure of the realism of a model or simulation; faithfulness. Fidelity should generally be described with respect to the measures, standards or perceptions used in assessing or stating it [4]. See accuracy, sensitivity, precision, resolution, repeatability.
2. The methods, metrics and descriptions of models or simulations used to compare those models or simulations to their real world referents or to other simulations in such terms as accuracy, scope, resolution, level of abstraction and repeatability. Fidelity can characterize the representations of a model, a simulation, the data used by a simulation (e.g., input, characteristic or parametric) or an exercise. Each of these fidelity types has different implications for the applications that employ these representations [4].
final condition
The values assumed by the variables in a component, system, model or simulation at the completion of some specified duration of time; final state [14, 15]. See boundary condition, initial condition.
final state
A final condition [4].
Resolution [1].
ground truth
The actual facts of a situation, without errors introduced by sensors or human perception or judgement [1, 14]. See truth.
A ranking or ordering of abstractions [23].
High Level Architecture
Major functional elements, interfaces and design rules, pertaining as feasible to all DoD simulation applications and providing a common framework within which specific system architectures can be defined [5, 20].
independent verification and validation
The conduct of verification and validation of a model or simulation by individuals or organizations that did not develop the model or simulation. IV&V does not require complete organizational independence but does imply a reasonable degree of organizational separation to assure unbiased analysis [5, 6, 14].
Any communication or reception of knowledge such as facts, data or opinions including numerical, graphic or narrative forms, whether oral or maintained in any medium including computerized databases, paper, microform or magnetic tape [17, 18, 24]. See knowledge, data.
information system
An interconnected collection of processing, communications and data storage components that collects, manipulates, stores, communicates and produces information for some purpose.
initial condition
The values assumed by the variables in a component, system, model or simulation at the beginning of some specified duration of time; initial state. See boundary condition, final condition [14].
1. An event external to a system that modifies the system in any manner [27].
2. A variable at the boundary of an organism or machine through which information enters; the set of conditions, properties or states that effects a change in a system's behavior [25].
3. Something introduced into a system or expended in its operation to attain a result or output [2]. See output, data.
4. The externally-supplied data to which a simulation responds and from which it calculates its output, e. g., operator controls, weapon detonation, wind speed and direction [4].
The representation of an abstraction by a concrete instance [13].
intelligent agent
A software entity that carries out a set of operations on behalf of a user with some degree of independence or autonomy and, in so doing, employs knowledge or representation of the user’s goals [13].
intelligent system
Any information system that builds or maintains internal state and behavior representations of the objects involved in its tasks and uses those representations to determine its behavior to execute those tasks to achieve a set of goals.
1. The ability for two individual systems to function coherently without creating results that occur only because the functionality of a single system is divided between them [1, 5, 8].
2. The ability of a set of models or simulations to provide services to and accept services from another models or simulations and to use the services so exchanged to enables them to operate effectively together and completely without anomaly [1, 5, 8].
1. The rules, environment, etc. that form the structure humans use to process and relate to information, or the information a computer system must have to behave in an apparently intelligent manner [13]. See information.
2. The sum or range of what has been perceived discovered or learned [2].
knowledge-based system
A system in which the domain knowledge is explicit and separate from the system’s operational instructions/information [13].
1. The observable delay between stimulus and response [4].
2. The time interval required by a simulation to respond to a stimulus in excess of the time interval required for the corresponding real world or standard event [4].
3. The time interval required for a device to begin output of data after presented with a stimulus or stimuli (e.g., input of data, occurrence of an event) [4].
littoral region
From seaward, the area from the open oceans to the shore that must be controlled to support operations ashore. From landward, the area inland from the shore that can be supported and defended directly from the sea [9].
1. A physical, mathematical or otherwise logical abstraction of a system, entity, phenomenon or process with its own assumptions, limitations and approximations [5, 8, 14, 20, 26]. See simulation, abstraction.
2. A geometry or feature assembly built in a relative coordinate system with the intent to multiply instances of the assembly at one or more world coordinate positions [9].
3. A system that stands for or represents another typically more comprehensive system [25].
Application of a standard, rigorous, structured methodology to create and validate a physical, mathematical or otherwise logical abstraction of a system, entity, phenomenon or process [10]. See model, abstraction.
modeling & simulation
The use of models, including emulators, prototypes, simulators and stimulators, either statically or over time, to produce results that support managerial or technical decision-making [13].
numerical stability
The property of an algorithm implemented on a computer that describes the growth of errors in the output due to that implementation.
A fundamental element of a conceptual representation for a federate that reflects reality at levels of abstraction and resolution appropriate for federate interoperability. For any given value of time, the state of an object is defined as the enumeration of all its attribute values [16].
object model
A specification of the objects intrinsic to a given system, including a description of the object characteristics or attributes and a description of the static and dynamic relationships that exist between objects [16].
1. Capable of being observed systematically or scientifically; discernible [2].
2. A physical property, such as temperature or weight, that can be observed or measured directly [2].
3. A state variable, computable by a function or functions, or mathematical relation(s) [4].
1. Any change produced in the surroundings by a system [25].
2. A variable at the boundary of an organism or machine through which information exits; the products, results or the observable parts of system behavior [25].
3. The data produced by a computer from a specific input [2]. See input, data.
4. The aspects of the simulated system being modeled; calculated during each pass in response to inputs and time passing, normally output for external use; values providing a snap-shot of the current state of the simulated system, e.g., position, velocity, alive-or-dead [4].
1. An observer's awareness or appreciation of objects, processes or situations in their environment mediated through their sensory organs [25].
2. An observer's descriptions, hypotheses or constructs of the world of which they become thereby a part [25].
3. To take notice of; observe [2].
1. The quality or state of being clearly depicted, definite, measured or calculated [12].
2. A quality associated with the spread of data obtained in repetitions of an experiment as measured by variance; the lower the variance, the higher the precision [12].
3. A measure of how meticulously or rigorously computational processes are described or performed by a model or simulation [4]. See resolution, sensitivity.
1. Something that affects entities (e.g., attrition, communications, and movement). Processes have a resolution by which they are described [27].
2. A system of operations in producing something [2].
3. A series of actions, changes or functions that achieve an end or result [2].
reconfigurable system
A system whose function can be changed to accommodate changes in its task, its surroundings or its own resources.
1. A codified body of knowledge about a thing being modeled or simulated [4].
2. Something referenced or singled out for attention, a designated object, real or imaginary or any class of such objects [2, 25].
The ability of the same observer to duplicate the results of an experiment or study [2].
1. Something that stands in place of or is chosen to substitute for something else (e.g., representation of constituencies in government, linguistic representation of an event) [14].
2. Something that describes as an embodiment of a specified quality [2].
3. The homomorphism of a group of abstract symbols into a group of more familiar objects [12].
4. A model or simulation [4].
The ability of an independent observer to duplicate the results from an experiment or study [28].
1. The degree of detail used to represent aspects of the real world or a specified standard or referent by a model or simulation [2].
2. Separation or reduction of something into its constituent parts; granularity [2].
1. A description of an exercise that is part of the database that configures the units and platforms and places them in specific locations with specific missions [14, 15].
2. An initial set of conditions and time line of significant events imposed on trainees or systems to achieve exercise objectives [14, 15].
3. An identification of the major entities that must be represented by the federation, a conceptual description of the capabilities, behavior, and relationships (interactions) between these major entities over time, and a specification of relevant environmental conditions (e.g., terrain, atmospherics). Initial and termination conditions are also provided [16].
4. A part of the modeling and simulation database that contains the force structure, its mission and plans, and the terrain area in which the simulated engagement occurs [27].
The range of real or imagined world objects or conditions represented by a particular model, simulation or simulation exercise [4].
semi-automated forces
Simulation of friendly, enemy and neutral platforms on the virtual battlefield in which the individual platform simulation are operated by computer simulation of the platform crew and command hierarchy. The term "semi-automated" implies that the automation is controlled and monitored by a human who injects command-level decision making into the automated command process [10]. See also computer-generated forces.
The ability of a component, model or simulation to respond to a low level stimulus [30].
The system being represented by a simulation [14]. See referent, model, simulation.
simulation exercise
The real-time execution of a simulation implementation [4].
1. A method, software framework or system for implementing one or more models in the proper order to determine how key properties of the original may change over time [4, 17]. See model, representation.
2. An unobtrusive scientific method of inquiry involving experiments with a model rather than with the portion of reality this model represents [17].
1. An accepted measure of comparison for quantitative or qualitative value; a criterion [2].
2. Proposition of a norm or general pattern to be followed when constructing, operating or testing a (technical) device. A standard contains a set of reference criteria for functional, structural, performance or quality aspects of a device or for any combination of these [25].
3. A rule, principle, or measurement established by authority, custom, or general consent as a representation or example [31].
state transition
A change from one state to another in a system, component or simulation [14].
state variable
A variable that defines one of the characteristics of a system, component or simulation where the values of all such variables define the state of the system, component or simulation [14].
1. The internal status of a simulation entity (e.g. fuel level, number of rounds remaining, location of craters) [14].
2. A condition or mode of existence in which a system, component, or simulation (e.g., the pre-flight state of an aircraft navigation program or the input state of given channel) [14].
3. The values assumed at a given instant by the variables that define the characteristics of a system, component, or simulation; system state [14]. See final state, initial state, steady state.
steady state
A situation in which a model, process or device exhibits stable behavior independent of time [14, 15].
Pertaining to a process, model or variable whose outcome, result or value depends on chance [14, 15]. See deterministic.
subject matter expert
An individual who, by virtue of education, training or experience, has greater than a journeyman’s expertise in a particular technical or operational discipline, system or process and has been selected or appointed to participate in the validation of a model or simulation [3].
A collection of components organized to accomplish a specific function or set of functions [15].
A classification system that provides the basis for classifying objects for identification, retrieval and research purposes [27].
The measurable aspect of duration. Time makes use of scales based upon the occurrence of periodic events. Time is expressed as a length on a duration scale measured from an index on that scale (e.g., 4 p.m.). Local mean solar time means that 4 mean solar hours have elapsed since the mean Sun was on the meridian of the observer [16].
1. The maximum permissible error or the difference between the maximum and minimum allowable values in the properties of any component, device, model, simulation or system relative to a standard or referent. Tolerance may be expressed as a percent of nominal value, plus and minus so many units of a measurement, or parts per million [30, 32, 32].
2. The character, state or quality of not interfering with some thing or action [32, 34].
1. Conformity to fact or actuality [2].
2. Faithful to an original or standard [2].
3. Reality; actuality [2].
4. A statement proven to be or accepted as true [2].
5. A property implicitly ascribed to a proposition by belief in or assertion of it; the denial is "falsity" [25].
6. In the verification theory of truth, a correspondence between the proposition and the events, properties or objects to which it refers linguistically or operationally [25].
7. In the logical theory of truth, the coherence between that proposition and other propositions [25].
8. In the constructivist theory of truth, constructability implying the absence of paradox and contradiction [25].
The individual, group or organization that employs or will employ the products or services from models, simulations or simulation federations to achieve their purposes. M&S users may be involved in the evolution of such products or services [3, 4].
V&V agent
The individual, group or organization designated by the V&V proponent to verify and validate a model, simulation or simulation federation. The V&V agent assures that the model or simulation meets the M&S requirements and provides sufficient information to the accreditation agent to support the recommendation to accredit a model, simulation or simulation federation for a specific purpose or intended use [3, 31]. See V&V agent.
The process of determining the degree to which a model or simulation accurately represents the real-world or some other meaningful referent from the perspective of the intended purpose of the model or simulation. Validation methods include expert consensus, comparison with historical results, comparison with test data, peer review and independent review [7, 26, 31]. See fidelity.
1. The quality of being inferred, deduced or calculated correctly enough to suit a specific purpose [4].
2. The quality of maintained data that is found on an adequate system of classification (e.g., data model) and is rigorous enough to compel acceptance for a specific use [4].
3. The logical truth of a derivation or statement based on a given set of propositions [30].
The process of determining that a model or simulation faithfully represents the developer's conceptual description and specifications. Verification evaluates the extent to which the model or simulation has been developed using sound and established software and system engineering techniques [8, 31]. See validation.


The references in this section are cited in the definitions given in the section above.

[1] RDE Forum, Glossary of Terms Applied to Fidelity, Simulation Interoperability Standards Organization, Orlando, FL, nd.
[2] Webster’s II New College Dictionary, Houghton Mifflin Co., Boston, MA, 1995.
[3] Personal communication with members of the DMSO VV&A Technical Support Team, 1999.
[4] The result of discussions within and comments from the SISO Fidelity ISG between March 1998 and December 1998.
[5] “Glossary,” Management of Army Models and Simulations, AR 5-11, US Department of the Army, Washington, DC, 8 March 2013.
[6] DoD Modeling and Simulation (M&S) Glossary, DoD 5000.59M, US Department of Defense, Washington, DC, January 1998.
[7] DoD Modeling and Simulation (M&S) Verification, Validation, and Accreditation (VV&A), Department of Defense Instruction, Number 5000.61, US Department of Defense, Washington, DC, 9 December 2009.
[8] Modeling and Simulation Master Plan, DoD 5000.59-P, US Department of Defense, Washington, DC, October 1995.
[9] SEDRIS Glossary, 29 June 1998, <at http://www.sedris.org/glossary.htm >.
[10] Systems Acquisition Manager’s Guide for the Use of Models and Simulation, Defense Systems Management College (DSMC), Defense Acquisition University, Ft. Belvoir, VA, September 1994.
[11] E. W. Weisstein, CRC Concise Encyclopedia of Mathematics, CRC Press, LLC, Boca Raton, FL, 1998.
[12] J. Daintith & R. D. Nelson, Dictionary of Mathematics, Penguin Books USA, Inc., New York, NY, 1989.
[13] Modeling and Simulation Glossary, Defense Modeling and Simulation Office, Alexandria, VA, January 1998.
[14] A Glossary of Modeling and Simulation Terms for Distributed Interactive Simulation (DIS), August 1995.
[15] IEEE Standard Glossary of Modeling and Simulation Terminology, IEEE Std 610.3-1989, Institute of Electrical and Electronics Engineers (IEEE), New York, NY, 1989.
[16] High Level Architecture Glossary, Defense Modeling and Simulation Office, Alexandria, VA, nd.
[17] Data Administration Procedures, DoD 8320.1-M, US Department of Defense, Washington, DC, 29 March 1994.
[18] Data Element Standardization Procedures, DoD 8320.1-M-1, US Department of Defense, Washington, DC, 15 January 1993.
[19] American National Dictionary for Information Systems, Publication 11-3, Federal Information Processing Standard (FIPS), Washington, DC, February 1991.
[20] “Navy Air Weapons Center Training Systems Division Glossary," M&S Educational Training Tool (MSETT), Navy Air Weapons Center, China Lake, CA, 28 April 1994.
[21] Military Handbook for Joint Data Base Elements for Modeling and Simulation (M&S), US Department of Defense, Washington, DC, 5 August 1993.
[22] The International Dictionary of Applied Mathematics, D. Van Nostrand Co., Inc., Princeton, NJ, 1960.
[23] Survey of Semi-Automated Forces, Defense Modeling and Simulation Office (DMSO), Alexandria, VA, 30 July 1993.
[24] Defense Information Management Program, DoD Directive 8000.1, US Department of Defense, Washington, DC, 27 October 1992.
[25] F. Heylighen, Web Dictionary of Cybernetics and Systems, nd, < at http://pespmc1.vub.ac.be/asc/indexASC.html >.
[26] VV&A Technical Support Team, Verification, Validation, and Accreditation (VV&A) Recommended Practices Guide, Defense Modeling and Simulation Office, Alexandria, VA, 1997.
[27] L.B. Anderson, SIMTAX: A Taxonomy for Warfare Simulation (SIMTAX), Workshop Report, Military Operations Research Society (MORS), Arlington, VA, 27 October 1989.
[28] Reproducibility, Wikipedia, < at https://en.wikipedia.org/wiki/Reproducibility >.
[29] TRADOC Modeling and Simulation Management Plan, U.S. Army Training and Doctrine Command, Ft. Eustis, VA, 31 July 1991.
[30] R.P. Turner & S. Gibilisco, eds., The Illustrated Dictionary of Electronics, 5th Edition, TAB Professional & Reference Books, Blue Summit, PA., 1991.
[31] M.J. Clugston, ed., The New Penguin Dictionary of Science, Penguin Books, London, UK, 1998.
[32] V. Neufeld & D.B. Gurlink, eds., Webster’s New World Dictionary of American English, 3rd College Edition, Simon & Schuster, Inc., Cleveland, OH, 1994.
[33] V. Illingworth, ed., The Penguin Dictionary of Electronics, 2nd Edition, Penguin Books, New York, NY, 1988.
[34] Funk & Wagnalls Standard Desk Dictionary, Volumes 1 & 2, Harper & Row Publishers, Inc., New York, NY, 1984.