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9 State of the Art with Respect to Military Needs I n this section we review the state of the art in individual, organizational, and societal modeling against the military modeling needs outlined in Chapter 2 and discuss the major shortfalls in meeting those needs. The five representative problems described in Chapter 2 are used as a structure to organize the review. DISRuPT TERRORIST NETWORKS One potential use of cultural and organizational models is to fuse par- tial and uncertain information from multiple sources to develop a model of the network structure of a terrorist organization and to use that model to evaluate alternative strategies for disrupting that organization, for example, through disconnecting leaders or interrupting recruiting. This goal can be supported by many of the modeling approaches described earlier, and each has its own limitations for attacking the problem. Table 9-1 summarizes the capabilities that would provide advantages for each modeling approach and the major limitations of the approach in addressing this problem. Network models provide a promising approach for this problem, but a general limitation across the network modeling approaches is the lack of data for model development. Lack of data is the primary challenge for using models to understand and disrupt terrorist networks. The data availability problem is compounded by the classification levels for existing data, the control of those classified data by multiple organizations, and the inconsistencies in data structure and content. For example, the same individual may be identified by different names in multiple databases. The 

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0 BEHAVIORAL MODELING AND SIMULATION TABLE 9-1 Modeling Approaches and Limitations for Disrupting Terrorist Networks Problem 1: Disrupt a terrorist network. How can we fuse uncertain and partial information from multiple sources to identify the dynamic network structure of a terrorist organization? How can we then best disrupt this network? Advantages of Approach Major Limitations Conceptual models indicate how removal Need ethnographic data on terrorists to see if of a leader will affect the network. models apply in the specific culture. Cognitive/affective models could predict Extensive time and effort are required to reactions of members of network if leader develop specific models from open sources. is removed. Organizational models of existing network Data are not available. Existing data are in could predict impact of changes in network multiple databases controlled by different on performance. organizations, with inconsistent structures and contents. Link analysis could identify network. Link data are difficult to acquire. Social network analysis models can predict how changes in leadership will affect network structure and change power and centrality. Dynamic network analysis models could Requires resource and activity data, which predict who the emergent leader will be if are very difficult to acquire. current leader is removed. System dynamics models could predict High-level model would not predict for whether change in leadership might lead to individuals. an increase in violence in the community. Model could be tested in massively Behaviors in the MMOG might not resemble multiplayer online games (MMOGs). those in the real world. All approaches could make No facility for rapid development of models recommendations for action. or provision of easy-to-understand guidance to war-fighters. more specific the predictions that could be made by the model, the more data are required. A way to mitigate this problem (see Chapter 11) would be to make unclassified representative databases more widely available for model development and evaluation. There is an additional challenge in how to test and validate these models and how to clearly communicate the uncertainty surrounding model forecasts. If models could be developed more quickly and easily and in closer collaboration with both subject matter experts and the ultimate users, they could be a more useful thinking tool for decision makers.

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 STATE OF THE ART WITH RESPECT TO MILITARY NEEDS FORECAST ADvERSARy RESPONSE TO COuRSES OF ACTION Models could be used to forecast the responses of adversaries to friendly force actions over a range of responses, with estimates of the likelihood of each. This is especially needed in urban operations and operations other than war in an asymmetric warfare environment in which conventional methods for predicting adversary behavior are often not relevant. For example, what are the likely reactions of both noncombatants and local insurgents to friendly force movements, and can those reactions be affected by the diffusion of information or disinformation? Table 9-2 summarizes the contributions that could be made by models and their major limitations. In the example of forecasting enemy response to a disinformation campaign about troop movements, network models are clearly applicable conceptually—the limitations are in the details that would make the model useful for a specific cultural context. First, we lack theory regarding cultural differences in the believability of a message as a function of its source. Multi- agent models could predict information diffusion patterns, but they would require data on transmission links (media channels, literacy rates, etc.) that are specific to the location and culture being modeled as well as ways to predict the believability of the message when received. Finally, there are no well-defined outcome variables for assessing the validity of the model’s TABLE 9-2 Modeling Approaches and Limitations for Forecasting Enemy Response to Disinformation Problem 2: Forecast adversary response to blue actions. Predict the likely response of noncombatants and local insurgents to friendly force movements, basing, logistics, and courses of action. Can disinformation be used to partially protect our intentions? What is the most effective point of insertion of the disinformation? Advantages of Approach Major Limitations Persuasion theory suggests the need to No models for how individuals are likely disconnect message from the source. to transform/distort messages as a result of Research exists on direction of change in cultural and cognitive factors. message with diffusion. There are no individual models to predict interpretation or believability of messages, especially taking cultural factors into account. Use multiagent model of networks to Multiagent models would require models decide where to drop information into of culture and technology to estimate speed rumor mill (e.g., viral marketing). of transition. Need to link multiple types of models together. Use model to maximize predicted diffusion Straightforward conceptually but there is a of information. lack of empirical country-specific data.

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 BEHAVIORAL MODELING AND SIMULATION predictions. Clearly the uses to which the model is to be put, including the details of the cultures and location of interest, must drive both its structure and content. As in the previous example, the major recommended mitiga- tion strategies (see Chapter 11) include the development and dissemination of detailed datasets and the development of a close collaborative relation- ship between model developers, subject matter experts, and model users. SOCIETAL FORECASTINg There is an urgent need for models that can forecast attitudes and behaviors at a societal level as a function of alternative courses of action particularly for diplomatic, information, military, and economic (DIME) campaigns. For example, models are needed that can forecast the stability of civilian governments and the incidence of violence as a function of these DIME factors. Table 9-3 summarizes the possible contributions and limita- tions of models for this goal. Agent-based models (ABMs) on a large scale appear very promising for modeling societal behaviors and forecasting responses to diverse DIME courses of action (COAs). However, there are a number of limitations that currently constrain what can be done with these models. First, such models are time-consuming to build and often require data collection on a massive level. Second, computational power limits the cognitive complexity that can be built into individual agents if tens of thousands of agents are to be included in the model. Third, predicting the response to integrated DIME COAs requires multidisciplinary expertise in military planning, economics, and political science. The need to integrate models across disciplines is the primary challenge faced in this problem area. Theories and models in these diverse disciplines are not currently integrated, and experts in these areas often have little opportunity or incentive to collaborate. Hybrid federated models that combine different models at different levels of detail for differ- ent factors offer considerable promise for tackling large-scale societal pre- diction, but these models are more an idea than a reality at present and will require the multidisciplinary development of architectures and standards for federation. To mitigate these limitations, Chapter 11 recommends an extensive multidisciplinary research program focused around common chal- lenge problems and datasets. Finally, as with other models, the predictions of these models will have a high degree of uncertainty. Model development must include collaboration between end users and diverse subject matter experts to ensure that the predictions provided are relevant and that their limitations are well understood.

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 STATE OF THE ART WITH RESPECT TO MILITARY NEEDS TABLE 9-3 Modeling Approaches and Limitations for Societal Forecasting Problem 3: Societal prediction. Forecast the effects of alternative diplomatic, information, military, and economic (DIME) courses of action on the attitudes and behaviors of residents in areas of interest. Advantages of Approach Major Limitations System dynamics models can predict the Sufficient theory is lacking to identify the key effects of changes in DIME factors on variables to be included in the model and to outcome variables of interest, such as level specify the connecting links between actions of violence. and outcomes. ABMs that capture resource use and ABMs need both theory and data to make economic interactions as well as social useful predictions. Large-scale societal ABMs links can predict the effects of economic are time-consuming and costly to develop. factors within a social and cultural context. ABMs can include tens of thousands of Agents must be cognitively simplistic to make agents to capture complex interactions at large-scale ABMs computationally feasible. the societal level. Historical data can be used to develop Prediction of the future, not the past, will ABMs that predict societal effects. involve inherent uncertainty. Federated models could integrate multiple There is a lack of infrastructure, types of models at different levels of detail architectures, and standards for federated to capture diverse DIME factors. models. DIME factors are studied by different disciplines and few integrated models exist that attempt to combine them. There is little theory or data on how DIME factors interact. MMOGs can provide an environment for The environment created by the MMOG may data collection on a large scale to support not reproduce the key elements of a real- model development and testing. world society. CROWD CONTROL TRAININg Virtual training environments offer an opportunity for troops involved in peacekeeping operations to learn best practices for crowd control. Such training will require models of noncombatants that respond to trainee actions in a way that is realistic and appropriate for a specific location and cultural environment. Table 9-4 summarizes the state of the art in this area. The development of models for crowd control training is perhaps the most advanced of the five representative problems considered. This can be done now. The only major issue is whether the models can produce behav- ior that is close enough to that of a real crowd in a specific environment to provide useful training. The extent to which cultural factors create differ- ences in crowd behavior in different locations deserves further study, but

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4 BEHAVIORAL MODELING AND SIMULATION TABLE 9-4 Modeling Approaches and Limitations for Crowd Control Training Problem 4: Crowd control training. Use models of crowd behavior to create a virtual training environment in which soldiers can learn to take the appropriate action. Advantages of Approach Major Limitations Cultural models can provide theory on Theory linking attitudes and behaviors may how crowd members in a specific culture not be specific enough for the environment are likely to react to different actions. for which training is needed. Cognitive and affective models can Individuals may react differently as part of represent individual reactions to soldier a crowd than they would alone. The effects behavior. of cultural context on behavior are not fully understood. ABMs can capture the interactions among Cultural variability in crowd dynamics is not crowd members that cause them to act completely understood. collectively in ways in which they might not have acted individually. MMOGs can provide an interactive Model behavior should be reviewed by environment for quickly testing model subject matter experts for believability. behavior as well as an environment for the training. crowd behavior models can be implemented in virtual environments, such as MMOGs, and their behavior can be reviewed by subject matter experts in a specific culture to ensure that they are not behaving in unrealistic ways that would result in negative training. ORgANIzATIONAL DESIgN: FORCE COMPOSITION AND COMMAND AND CONTROL ARCHITECTuRE Because of the rapid changes in mission requirements, the military services are moving toward modular expeditionary forces that are readily reconfigurable for different types of missions. Making the best use of these modular forces requires not only a recommended force composition (sys- tems, equipment, units, and personnel) but also a command and control (C2) architecture that is most effective for the force as constituted. The best force composition and C2 architecture for a conventional military opera- tion may be quite different from that for a peacekeeping or disaster relief mission. Table 9-5 summarizes how organizational models could help in this process.

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5 STATE OF THE ART WITH RESPECT TO MILITARY NEEDS TABLE 9-5 Modeling Approaches and Limitations for Organizational Design Problem 5: Organizational design: Force composition and command and control architecture. Use organizational models to develop optimal force composition packages and C2 architectures for different mission types. Advantages of Approach Major Limitations Use organizational models to develop the Requires detailed data on the tasks to be force composition, structure, and processes performed in the mission and the resources that are predicted to best meet mission available. requirements. Simulate organizational performance for different structures in different mission scenarios. Use simulation and ABMs to identify the Requires detailed data on task information points in the mission and the organization and workload requirements. at which the most intensive cooperation will be required, the points of maximum workload, and the potential information bottlenecks. Use MMOGs as a testbed for May be difficult to replicate realistic mission organizational structures. tasks and conditions. Models have proven to be a useful tool for understanding, designing, and testing organizations. Although people rarely think about “designing” organizations in a systematic way, the military faces the need to do just that as it develops new flexible, adaptive structures for rapidly changing mis- sions. One example of an attempt at systematic organizational design based on modeling is the recent effort at the National Aeronautics and Space Administration (Carroll, Gormley, Bilardo, Burton, and Woodman, 2006), using an ABM and a heuristic rule-based model. Modeling and simulation can be used to develop and adapt force composition for changing mis- sions and to suggest the best C2 structure for accomplishing the mission. The best C2 architecture is especially challenging for coalition operations, in which different types of forces may be involved, and for peacekeeping and disaster relief operations, which require close coordination with non- government organizations. The major limitation for this work is the need for detailed information on the tasks to be accomplished in the mission and the resources required to accomplish those tasks. The recommended miti- gation strategy (see Chapter 11) is the development of common challenge problems and datasets and the use of collaborative workshops to ensure that that operational users and modelers have a shared understanding of what can be done through modeling.

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 BEHAVIORAL MODELING AND SIMULATION REFERENCE Carroll, T.N., Gormley, T.J., Bilardo, V.J., Burton, R.M., and Woodman, K.L. (2006). Design- ing a new organization at NASA: An organization design process using simulation. Organization Science, , 202–214.