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2
Military Missions and
How IOS Models Can Help
C
omputational modeling and simulation (M&S) technology have
long been useful military tools, although these models have focused
primarily on physical effects, such as the predicted capabilities of
sensors or weapons systems. Today, the changing nature of military mis-
sions is driving the need for new types of computational models that focus
on human behavior, specifically on human behavior in social units, such as
organizations and societies.
The military has traditionally made use of computational modeling in
three broad areas of activity:
. Analysis and forecasting for planning. Models are used for the
fusion of fragmented and incomplete information about enemy
activities and capabilities. For example, models of enemy equip-
ment can be used to interpret fragmentary data on the performance
of that equipment (e.g., what capabilities in the equipment could
have resulted in the observed performance). Forecasting models are
used to develop courses of action (COAs) based on the desired out-
comes and their estimated likelihood of achieving those outcomes.
At a simple level, for example, models are used to forecast the
effectiveness of different types of weapons against different kinds
of targets.
. Simulation for training and rehearsal. Models are used in simula-
tions that create training and rehearsal environments. For example,
pilots practice complex and dangerous combat maneuvers in simu-
lators before encountering them in exercises or combat, and tank
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4 BEHAVIORAL MODELING AND SIMULATION
commanders practice ground combat missions before an actual
engagement. In both situations, considerable effort goes into model-
ing the environment (e.g., aerodynamics and terrain), simulating the
dynamics of the friendly and enemy sensors and weapons systems,
and providing the critical performance feedback to trainees needed
for skill improvement and “learning to criterion.”
. Design and evaluation for acquisition. When a system is designed,
built, and acquired, models are used throughout the process to pre-
dict performance and make design decisions based on cost-benefit
trade-offs. For example, detailed physical and electronic models
can be used to predict the additional range of a sensor accruing
from a proposed enhancement (and increased cost), to support a
cost-benefit trade-off.
In this chapter we argue that the successful performance of all three
of these activities in today’s military environment requires not only the
traditional set of physically based models and simulations now used, but
also computational models of human behavior, particularly computa-
tional models of human behavior in social units. We begin by describing
today’s changing military missions in order to explain why—in the current
environment—analysis, planning, training, and acquisition require models
of human behavior at many levels: at the individual level, at the team or
organizational level, and at the societal level. We then give specific examples
of how these individual, organizational, and societal (IOS) models could
be used by the military. Finally, we briefly review current military IOS
modeling efforts and summarize the major challenges involved in meeting
current needs. Subsequent chapters provide a broader review of state-of-
the-art IOS behavioral modeling approaches, assess the extent to which
those approaches have the potential to meet military needs, identify major
shortfalls and gaps, and recommend a plan of action to address them.
MILITARy MISSIONS NOW AND INTO THE FuTuRE
This section reviews the changing nature of today’s military missions
to explain why effective forecasting, training, and acquisition require com-
putational IOS models.
Overarching Strategy and Operational Enablers
The changing nature of current and future military missions is made
quite explicit in the Department of Defense’s (DoD) Quadrennial Defense
Review (U.S. Department of Defense, 2006). Coming out of a long tradition
of “attrition-based” conventional warfare and backed ultimately by nuclear-
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5
MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
based mutual assured destruction (MAD), DoD is now undergoing a shift
of tectonic proportions to operationalize the National Defense Strategy of
“fighting the long war” and has identified five critical operational enablers:
. Defeating multinational multiethnic terrorist networks that “seek
to break the will of nations that have joined the fight alongside
the United States by attacking their populations” and “use intimi-
dation, propaganda and indiscriminate violence in an attempt to
subjugate the Muslim world under a radical theocratic tyranny”
(U.S. Department of Defense, 2006, p. 13).
. Defending the homeland in depth against both terrorist networks
and hostile states with weapons of mass destruction (WMD) capa-
bilities. Globalization enables “the spread of extremist ideologies”
and “the movement of terrorists” and “empowers small groups and
individuals” with the result that “nation-states no longer have a
monopoly over the catastrophic use of violence” (U.S. Department
of Defense, 2006, p. 36).
. Shaping the choices of countries at strategic crossroads to protect
the “future strategic position and freedom of action of the United
States, its allies and partners” by shaping the choices of “major and
emerging powers . . . in ways that foster cooperation and mutual
security interests” (U.S. Department of Defense, 2006, p. 39). In
addition to the Middle Eastern region, countries of particular con-
cern are India, China, and Russia.
4. Preventing the acquisition or use of WMD by hostile states (e.g.,
Iran) or nonstate actors (e.g., Osama bin Laden). “Based on the
demonstrated ease with which uncooperative states and non-state
actors can conceal WMD programs and related activities, [we]
must expect further intelligence gaps and surprises” (U.S. Depart-
ment of Defense, 2006, p. 45).
5. Refining DoD’s force planning construct for wartime to move grad-
ually from a two-front conventional campaign capability to more
loosely defined “distributed, long-duration operations, including
unconventional warfare, foreign internal defense, counterterror-
ism, counterinsurgency, and stabilization and reconstruction opera-
tions” (U.S. Department of Defense, 2006, p. 36).
This is a remarkable shift in emphasis since the terrorist attacks in the
United States on September 11, 2001, and may very well be a turning point
away from more than 50 years of conventional force planning (backed by
MAD) and the start of a much more agile and indigenously sensitive force.
The United States is no longer fighting nation-states using conventional
weapons but instead is fighting a very different kind of organization—
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BEHAVIORAL MODELING AND SIMULATION
terrorist networks—in a battlespace in which effects may be defined by the
attitudes and behaviors of civilian noncombatants rather than by bombs on
targets.1 In order to analyze, plan, train, and acquire effective technology
for this new battlespace, models are needed to help people understand and
interpret fragmentary information about terrorist activities and understand
the likely effects of U.S. actions on the attitudes and behaviors of diverse
multicultural civilian populations. People need to understand the forces that
drive individuals to join terrorist organizations, how these organizations
function, and how they organize action. People need to understand the
factors that contribute to the stability of neighborhoods and regions and
how military actions as well as political, diplomatic, and economic actions
contribute to that stability. People need to understand complex shifting
cultural allegiances and how U.S. actions affect those allegiances. Models
of sensor and weapons systems are not adequate tools for fighting this long
war. The nation’s defense planners need IOS models that capture the rich-
ness of individual, team, organizational, societal, and cultural influences
that can help to address the key dimensions of the new battlespace.
Dimensions of the New Battlespace
In this section we examine some of the drivers of the changing DoD
mission to gain insight into what this shift in mission means for IOS model-
ing requirements.
The Impact of urbanization
One of the key drivers in this shift has been the growing recognition
that fundamental world demographics are changing: “The world’s urban
population reached 2.9 billion in 2000 and is expected to rise to 5 billion
by 2030. Whereas 30 per cent of the world population lived in urban areas
in 1950, the proportion of urban dwellers rose to 47 per cent by 2000 and
is projected to attain 60 per cent by 2030. . . . At current rates of change,
the number of urban dwellers will equal the number of rural dwellers in the
world in 2007” (United Nations, 2002, Part I, p. 5). The military implica-
1 A note of caution is appropriate here. Although it is true that at the time of this writing the
United States is not engaged in a conventional war, that is not to say that it will not be engaged
in one at some point in the future. Thus, there is always the danger that the nation will be
“preparing for the last war” (e.g., today’s Afghanistan and Iraq campaigns) via a wholesale
shift in focus to nonconventional strategies, tactics, and weapons systems. DoD recognizes
this, as noted in the fifth “operational enabler” cited above (U.S. Department of Defense,
2006, p. 36), identifying the desire to “move gradually [emphasis added] from a two-front
conventional campaign capability. . . .” Clearly, the operative issue is how long this transition
takes and to what extent it transforms the services’ force structure.
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
tions of this fact are explored in depth in two recent RAND studies (Glenn,
2000; Vick et al., 2002). Key issues and implications that emerge from these
studies and others include:
• Most, if not all, of the future conflicts the nation will face will have
an urban component, based both on historic precedent and on the
fact that the adversaries are no match for U.S. forces in “open
field” engagements.
• It will no longer be sufficient to avoid urban and surrounding
built-up areas during military operations, as has so long been U.S.
doctrine. According to a 2002 Joint Chiefs of Staff report, “urban
areas are the natural battleground for terrorists: the effects of ter-
rorist acts are greater and more noticeable and the terrorist groups
more difficult to locate and identify” (Joint Chiefs of Staff, 2002,
p. III-27). From a “hearts and minds” standpoint, there is also a
clear political advantage of having a close connection with the
noncombatant urban population.
• Urban operations are extremely difficult, with the operational
environment characterized by high densities and tempos, inherent
complexity, and constraints. The battle tempo can be extremely
high, forcing rapid assessments, decisions, and actions. Collateral
damage issues covering critical infrastructure losses, damage to
symbolic edifices, and noncombatant loss of life are critical.
Urban operations are also complicated by the fact that mission objec-
tives can vary dramatically in both time and space, running from all-out
conflict to infrastructure rehabilitation. This spatiotemporal nonuniformity
has been referred to as the “three-block war” by the former commandant
of the Marine Corps, General Charles C. Krulak: “In one moment in time,
our service members will be feeding and clothing displaced refugees, provid-
ing humanitarian assistance. In the next moment, they will be holding two
warring tribes apart—conducting peacekeeping operations—and, finally,
they will be fighting a highly lethal mid-intensity battle—all on the same
day . . . all within three city blocks. It will be what we call the ‘three block
war’” (Krulak, 1997, p. 139).
In these stability and support operations (SASO) stages, it becomes
increasingly important to interact with and not alienate the local popula-
tion, get their support to identify social networks of adversaries (and poten-
tial allies), and anticipate first- and second-order effects (i.e., unintended
consequences) of actions that are within the scope of the unit’s capabili-
ties (i.e., executing a search-and-destroy mission) but that may be highly
counterproductive in the long run. It also follows that as the mission
becomes dictated less by military objectives than by social and political
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BEHAVIORAL MODELING AND SIMULATION
objectives, there is a need to ensure greater interaction with other orga-
nizations outside the local unit’s normal sphere of interest. Not only does
this imply a greater reliance on joint operations (coordinating the sister
services), and increasingly a reliance on coalition (non-U.S.) partners, but
it also implies greater interagency coordination, both national (e.g., the
State Department, the intelligence agencies, the organs of public diplomacy,
U.S.-based nongovernmental organizations or NGOs), international (e.g.,
sister intelligence services, non-U.S. NGOs), and private-sector economic
interests. As a consequence, in order to address and achieve the peacemak-
ing objectives in the new theaters of war, planners must somehow consider
and assess the aggregated complex interactions of entire social systems,
both regional in behaviors and global in influence, at resolutions of fidelity
neither needed nor attempted in prior military history.2
The objectives and technologies of peacemaking in this environment
are very different from those of conventional warfare, most notably, a sub-
stantially increased emphasis on peacekeeping, disaster relief, and nation-
state building (see, for example, the Urban Sunrise study of the Air Force
Research Laboratory, 2004). The urban operational environment serves to
transform what was once viewed as a strictly military (and tactically diffi-
cult) engagement into something that is now considerably more holistic and
focuses primarily on social, organizational, and cultural factors involving
key individuals, nonmilitary groups, local crowds, and indigenous popula-
tions, all within a rich tapestry of a complex local infrastructure overlaid
by local, national, and transnational economic markets, organizational and
social structures, traditions, cultures, and religious beliefs.
The growing Importance of Pre- and Postconflict Operations
The changing nature of military missions is putting increasing focus
on operations that occur before and after periods of overt conflict. These
pre- and postconflict operations may persist much longer than the conflict
itself, as is all too well illustrated by the current situation in Iraq.
In the doctrine for Joint Urban Operations (JUO) (Joint Chiefs of Staff,
2002) five phases are recognized—understand, shape, engage, consolidate,
and transition (USECT, emphasis added):
2 While the military is the branch of the U.S. government having primary responsibility for
projecting U.S. power overseas, it may be a classic case of “mission creep” for the military to
be taking a leading role in economic development, political reconstruction, diplomacy, disaster
relief, and intercultural communication. But this is exactly what is happening in today’s con-
flicts, with young servicemen serving effectively as “mayors” of Iraqi villages, see http://www.
washingtonpost.com/wp-dyn/content/article/2007/01/11/AR2007011101576.html. And this is
likely to remain the case until other U.S. agencies or NGOs can take the lead, or the United
States successfully transitions these functions back to the local population.
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
. Understand: “The JFC [joint forces commander] evaluates the
urban battlespace, including the urban triad [the physical terrain,
the urban infrastructure, and the population] and the threat, to
determine the implications for military operations. This evalua-
tion extends from complex terrain considerations to the even more
complex impact of the sheer number of actors operating in an
urban battlespace. On one hand there may be adversary military
troops, criminal gangs, vigilantes, and paramilitary factions oper-
ating among the noncombatant population. On the other hand,
especially in MOOTW [military operations other than war], the
situation may be further complicated by the presence of nonmilitary
government departments and agencies, to include intelligence, law
enforcement, and other specialized entities” (Joint Chiefs of Staff,
2002, Chapter II, pp. 8-9).
. Shape: “Shaping includes all actions that the JFC takes to seize the
initiative and set the conditions for decisive operations to begin.
The JFC shapes the battlespace to best suit operational objectives
by exerting appropriate influence on adversary forces, friendly
forces, the information environment, and particularly the elements
of the urban triad. Methods of shaping may include . . . the phased
deployment and employment of joint forces. Rather than deploying
combat forces initially, the JFC may, in many cases, need to deploy
noncombat forces early, such as civil affairs (CA), public affairs
(PA), medical support, and psychological operations (PSYOP) units.
. . . Critical to shaping operations is the isolation of the urban area
to support the campaign” along physical, informational, and moral
dimensions (Joint Chiefs of Staff, 2002, Chapter II, p. 11).
. Engage: “To engage, the JFC brings the full dimensional capabilities
of the force to bear in order to accomplish operational objectives.
Engagement can range from full combat in war to FHA [foreign
humanitarian assistance] and logistic support for disaster relief
operations. It consists of those actions taken by the JFC against
a hostile force, a political situation, or a natural or humanitarian
predicament that will most directly accomplish the mission. In all
cases, the speed and precision with which the JFC engages will
largely determine any degree of success. . . . [S]uccessful engage-
ment requires . . . the seizure, disruption, control, or destruction of
the adversary’s critical factors,” which include their “capabilities,
requirements, and vulnerabilities” and may include
o “tangible components of the infrastructure such as power
grids, communications centers, transportation hubs, or basic
services.”
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0 BEHAVIORAL MODELING AND SIMULATION
o “intangible socio-economic or political factors such as financial
centers and capabilities, particular demographic groups and
sites, and cultural sensitivities.”
In addition, “both offensive and defensive JUOs will probably entail
heavy use of IO [information operations] and CMO [civil military
operations]” (Joint Chiefs of Staff, 2002, Chapter II, p. 12).
4. Consolidate: “In war and MOOTW, the focus of consolidation
is not just on protecting what has been gained, but also retaining
the initiative to disorganize the adversary in depth. . . . Consolida-
tion may place heavy emphasis on logistic support and CMO. The
nature of the urban triad ensures that the JFC will have to contend
with issues concerning physical damage, noncombatants, and infra-
structure as part of consolidation. CMO and PSYOP units may
continue to be especially critical in this aspect, as well as engineer-
ing efforts ranging from destruction to repairs to new construction.
Equally important are the expected issues of infrastructure collapse
and the tasks of FHA and disaster relief” (Joint Chiefs of Staff,
2002, Chapter II, pp. 12-13).
5. Transition: “In general, the end state of JUOs is the termination
of operations after strategic and operational objectives have been
achieved. This may include the transfer of routine responsibilities
over the urban area from military to civilian authorities, another
military force, or regional or international organizations. . . . In
JUOs, transition may occur in one part of an urban area while
engagement still is going on in another [three-block war]” (Joint
Chiefs of Staff, 2002, Chapter II, p. 13).
Note the overall emphasis on the social and organizational interactions
of a diverse set of actors, including noncombatants, noncombat forces,
and local and multinational civilian agencies. There is also a focus on the
effects of informational, socioeconomic, and political factors on attitudes
and behaviors in the urban battlespace.
Changes in the Nature and Scale of Intervention Operations
Urbanization and the broader view of military USECT interventions
yield a dramatic expansion of considerations of scale, in both spatial and
temporal dimensions, as well as an expansion in the nature and types of
intervention to be considered.
In the spatial dimension, urban operations demand a much finer view of
the battlespace: it is no longer sufficient to consider high-level aggregates of
large units and large geographic areas of responsibility, such as one might do
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
in planning conventional operations at the division level and above. Instead,
the urban domain demands a block-by-block (if not building-by-building)
geographic focus, at squad-level units consisting of only a few individual
soldiers. At the other end of the spectrum, the broad considerations of
USECT phasing of an engagement call for understanding wide-ranging
geopolitical factors, including the nation-states involved, and the associated
ethnic, cultural, religious, and economic factors in the region. These are typi-
cally not small or geographically focused but may in fact encompass huge
spatial overlay regions of the potential battlespace (e.g., the Middle East). As
a consequence, there are simultaneous demands to have a very fine spatial
focus (at, say, the building level) while simultaneously being highly sensitive
to the very large regional characteristics of the battlespace.
In the temporal dimension, a similar situation exists. The fine-scale
urban focus, with its short “interaction distances,” typified by an impro-
vised explosive device (IED) or a rocket-propelled grenade, demand a very
fine-grained temporal view of events for assessment, planning, and execu-
tion. Planning horizons are short, and urban operations demand a high
temporal resolution of activities if operations are to succeed.3 The time
available to plan operations is likewise compressed, and planning windows
are compressed, often down to minutes. At the other end of the spectrum,
USECT phases can take months or years to accomplish and are often char-
acterized by considerably slower temporal dynamics and windows, in both
the planning and the execution of activities. Thus, as in the situation with
the spatial dimension, there is a simultaneous stretching of the temporal
dimension from both ends, from very quickly occurring events at a high
temporal resolution (e.g., building clearing), to activities that evolve at a
considerably slower pace, demanding low temporal resolution but long time
horizons (e.g., nation building).
A key issue for modeling IOS behavior is the spatiotemporal “cover-
age” that must be accommodated in models. One can clearly no longer
expect that a high-level aggregate model of, say, an armored division cov-
ering miles of open plain will be up to the challenge of anticipating the
outcome of a fast-paced short-range small-unit urban engagement. Nor will
the small-unit model be any indicator of overall outcome in the big picture
of the overall military engagement. And neither is up to the challenge of
anticipating outcomes in the larger USECT tableau, with its many other
dimensions beyond the application of military force.
Growth of the spatiotemporal scale is also accompanied by an expan-
sion of intervention options available in urban operations over the several
USECT phases. This is a natural consequence of the additional dimensions
3 Thisis perhaps best illustrated with the detailed step-by-step choreography that goes into
the planning of a simple room clearing by a four-man squad.
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BEHAVIORAL MODELING AND SIMULATION
and structures that make up the urban environment and its indigenous
population, as illustrated in the deliberately simplified three-layer struc-
ture of Figure 2-1. Shown here is the conventional physical structure (and
infrastructure) that is the focus of traditional military campaigns, on which
is superimposed an information structure associated with elements of the
underlying physical entities, in turn superimposed by a cognitive struc-
ture characterized by individual and group perceptions, beliefs, intentions,
plans, and actions (Air Force Research Laboratory, 2004).
The focus for planning military operations is increasingly on under-
standing and forecasting4 “nonkinetic” effects. Kinetic effects are associ-
ated with the use of “kinetic weapons”—conventional bullets and bombs.
Nonkinetic weapons and defenses are associated primarily with IO, which
include the triad of electronic warfare, computer network operations (both
defensive and offensive), and influence operations, which include PSYOPS,
military deception, and operations security (OPSEC). Nonkinetic options
also include the use of nonlethal weapons at the individual or crowd level
(e.g., high-powered microwaves) and at the population level (e.g., disabling
or destroying one or more components of, say, an urban infrastructure).
In this expanded battlespace, planning and executing effects-based oper-
ations (McCrabb, 2001) require analysis of the potential effects that a given
set of diplomatic, information, military, and economic (DIME) actions will
have across the full range of the political, military, economic, social, infor-
mation, and infrastructure (PMESII) context. To be useful for analysis and
planning, behavioral models must capture not only the separate effects of
each action in each of these areas but also the interactions of these factors.
HOW IOS BEHAvIORAL MODELS CAN HELP THE MILITARy
The changing nature of DoD’s mission has greatly increased the need
for IOS models that capture the cognitive, organizational, societal, and
cultural factors that are critical in the urban battlespace. IOS models are
needed across the full spectrum of operations, particularly during urban
4 We introduce the term “forecasting” here, in place of predicting, to reemphasize the difficult
problem of anticipating individual or organizational behavior (see Chapter 1), in comparison
to that of anticipating the consequences of well-understood physical or engineering laws, the
latter operating under conditions in which there is neither agency nor feedback involved (e.g.,
when you swing a hammer, the hammer does not deliberately try to avoid the nail in order to
dissuade you from further swinging, so that your dynamic model of the muscle-hammer system
is reasonably “predictive”). The term “forecasting” is also loaded with weather analogies,
serving to remind us of how weather “point predictions” (in time and space) are almost always
wrong and how “bounding envelope forecasts” are much more likely to capture the future
trajectory of the weather, especially as the spatial and temporal resolution grows more coarse
(i.e., with larger geographic areas covering “climate zones” and longer time windows covering
“seasonal variations”). See also the extensive discussion of forecasting in Chapter 8.
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
Pools of beliefs,
intents, plans, and
COAs
Cognitive
Structure
Cultural
Intelligence
Domain
Inform
ation S
tructu
re
GeoSpatial
Intelligence
Domain
Phy
sica
l Str
uctu
re
FIguRE 2-1 Heterogeneous structures that must be represented in the urban
environment.
SOURCE: Air Force Research Laboratory (2004, p. 10).
operations, as indicated by the number one recommendation of the recent
Joint Urban Operations Workshop: “Employ high-resolution modeling,
simulations, and other decision support tools that incorporate friendly,
enemy, and neutral forces, plus the urban population in order to conduct
rehearsals, assess courses of action, and make better decisions faster than
the enemy in an urban operation” (Mahoney, 2005).
This section reviews how IOS models can contribute to today’s missions
in the three broad areas: (1) analysis and forecasting for planning, (2) train-
ing and rehearsal, and (3) design and evaluation for acquisition. Another
view of such applications is found in Axelrod (2004).
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BEHAVIORAL MODELING AND SIMULATION
Appendix TABLE 2-A1 Continued
Acronym
Acronym Expansion Description
PCAS Pre-Conflict A recently concluded DARPA program to investigate
Anticipation and the effectiveness of different computational social
Shaping science approaches to support forecasting the
likelihood of a nation-state failure (e.g., Sudan).
The PCAS architecture consists of four modules for
data collection, modeling, gaming/shaping tools,
and decision support tools. Computational modeling
approaches include system dynamics, multiagent
systems, Bayesian influence models, diffusion models,
and regression modes.
PMFServ Performance An integrated framework that permits one to
Moderator examine the impacts of stress, culture, and emotion
Function Server on decision making. PMFServ has been used to create
and simulate the people and objects of a number
of scenarios, including crowd scenes (civil unrest in
the United States, urban conflict in the Mideast),
asymmetric threat leaders and followers, the Black
Hawk Down recreation in the UnrealTournament™
game engine, and world leader modeling in a
diplomacy and strategy game. Over the past 5 years
the instructor has been sponsored by DMSO, ONR,
IDA, GM, Army, DARPA, JFCOM, and others.
RAID Real-time Supports real-time forecast analysis of probable
Adversarial enemy actions in urban operations against irregular.
Intelligence and RAID leverages novel approximate game-theoretic
Decision-making and deception-sensitive algorithms to continuously
identify and update forecasts of likely enemy actions
while continuously estimating likely deceptions in the
available battlefield information. Significant effort
in the program is being applied to evaluating the
program’s performance relative to that of human
analysts unaided by RAID.
SAMPLE, Situation SAMPLE is a cognitive architecture comprised of
GRADE Awareness Model modules for fuzzy rule-based perception, Bayesian
for Person in the belief network-based situation awareness, and
Loop Evaluation, production rule-based decision making. GRADE is an
Graphical Agent agent development environment for rapidly creating
Development SAMPLE models for different domains/tasks. Both
Environment have been used with JSAF, IWARS, the EAAGLES air
combat simulation, the FACET ATM simulation, and
the UnrealTournament™ gaming engine.
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
Sponsor/
Category Research Center Reference/Website
Nation-state DIME/ DARPA/IXO (Popp et al., 2006)
PMESII modeling
methodologies
Cognitive University of http://www.seas.upenn.edu/~barryg/
architecture for Pennsylvania, HBMR.html
individual entity DMSO, ONR, IDA,
modeling and U.S. Army, DARPA,
associated agent JFCOM
development
environment
Decision aiding tool DARPA IIXO http://dtsn.darpa.mil/IXO/
with game-theoretic programs.asp?id=43
model for adversary (Kott and Ownby, 2005)
behavior forecasting
Cognitive AFOSR, AFRL, http://www.cra.com
architecture for ARL, DARPA, NRC, (Harper, Ton, Jacobs, Hess, and
individual entity NSSC, ONR Zacharias, 2001)
modeling and
associated agent
development
environment
continued
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0 BEHAVIORAL MODELING AND SIMULATION
Appendix TABLE 2-A1 Continued
Acronym
Acronym Expansion Description
SEAS Synthetic An agent-based software development environment
Environments that incorporates seven behavioral primitives:
for Analysis and initiate, search, decide, execute, communicate,
Simulation update, terminate. No attempt is made to model
fundamental cognitive or social behavioral models,
but a capability is provided for representing entities
at the individual, organizational, and institutional
level. Developers claim that the SEAS environment
integrates multiple theories from various disciplines
to program behaviorally accurate agents, but little
has been available in peer-reviewed journals to
substantiate that claim. JFCOM has been a strong
supporter, especially in the attempts to model large-
scale, nation-state-level projections (DIME/PMESII
input-output forecasts) and COA assessments.
SIAM Situational A collaborative decision aiding tool to help multiple
Influence analysts and experts decompose and analyze complex
Assessment Model problems. It consists of a user-friendly graphical
interface that supports the development and
exercising of influence networks, a utility function
decision-theoretic approach that builds on belief
networks. SIAM allows each factor or influencing
relationship affecting a decision to be examined
separately, yet it optimizes understanding of the
overall impact of, and the interrelationships among,
the contributing factors.
Soar, Simulation of Soar is an operator modeling production rule system
Soar-EPIC Adaptive Resource, in which existing rules propose potential operators
Executive-Process/ that might be used to solve the current goal or
Interactive Control problem. It is focused on problem solving and has
its roots in GOMS. Its lack of a perceptual front end
and motor back end has motivated hybridization
with EPIC to provide these services. Although its
psychological basis is less well-developed than other
research-oriented models, Soar has been applied to a
number of military systems modeling efforts (notably
TacAir Soar).
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
Sponsor/
Category Research Center Reference/Website
Software agent- Simulex, JFCOM http://www.simulexinc.
based development com/products/case_studies/#seas-vis
environment
Visualization and SAIC http://www.saic.com/business/technologies/
decision aiding tool license/it/siam.Pdf
Operator modeling University of http://sitemaker.umich.edu/soar/home,
production rule Michigan, SoarTech http://www.soartech.com
system
continued
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BEHAVIORAL MODELING AND SIMULATION
Appendix TABLE 2-A1 Continued
Acronym
Acronym Expansion Description
SPECTRUM Provides an environment with multicolored,
multisided icons in an effort to simulate realistic
situations that is conducive to MOOTW (SASO).
SPECTRUM portrays the graphics and terrain of
this environment and adds the human dimension,
to account for the impact of economics, politics,
regional populations, nongovernmental agencies
(NGOs), and humanitarian relief agencies.
SROM Stabilization and Analyzes the organizational hierarchy, dependencies,
Reconstruction interdependencies, exogenous drivers, strengths, and
Operations Model weaknesses of a country’s PMESII systems using
systems dynamics modeling techniques. SROM
models a country in a holistic lumped parameter
manner as a national submodel, which is then defined
in terms of its n regions as a system of systems.
Each regional submodel itself contains six functional
submodels: demographics submodel, insurgent and
coalition military submodel, critical infrastructure,
law enforcement, indigenous security institutions, and
public opinion.
STELLA A simulation-based training environment to train
soldiers in information operations. A cognitive model
was constructed using Bayes inference nets and
neural nets to guide combat models based on internal
logic. At the time of this review, fuzzy set theory was
being contemplated for modeling the propagation
of rumors, and a mathematical submodel of IW was
being developed using q-analysis and Boolean nets to
study the structure and dynamics of IW.
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MILITARY MISSIONS AND HOW IOS MODELS CAN HELP
Sponsor/
Category Research Center Reference/Website
Sociocultural training National Simulation http://www.msrr.army.mil/
system Center (NSC)
DIME/PMESII USAF AFRL/IF (Robbins, Deckro, and Wiley, 2005)
regional or nation-
state modeling
environment
Information warfare DISA, AFAMS http://www.disa.mil/
training system
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4 BEHAVIORAL MODELING AND SIMULATION
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