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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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