DYMATICA assesses state/non-stage domain types: full spectrum warfare, counterterrorism, humanitarian crises, and asymmetric behaviors.
Focus of DYMATICA
DYMATICA is designed to help answer why a country or group of interest is doing what they are doing and anticipate how they would respond to a US or allied course of action (COA) or policy.
DYMATICA analyzes such things as geopolitical gamesmanship, regular and irregular warfare, targeted propaganda, the weaponizing of information, and economic, political, and societal stability to produce descriptive and prescriptive analytics. One of the information sources could be social media and other data.
A typical DYMATICA assessment shows how different scenarios and courses of action (COA) are likely to affect key outcomes (subject to a variety of causal hypotheses) over time. Depending on the situations of interest, these outcomes may be geopolitical, such as interactions between countries of interest (COI), at the group level (such as political leanings of various groups, or tendencies of groups to engage in conflict or social unrest or to support U.S. actions), and individual level (such as decisions made by leaders). Output can also be non-cognitive (such as resource availability or economic trends). Structural and parametric uncertainty can be incorporated to demonstrate the range of likely outcomes given a variety of potential
- Various forms of information can be used to populate a DYMATICA model such as a country’s economic wellbeing, its military potential, the sentiment within the country, along with report documents and SME guidance.
- Reports, data, and SME guidance provide the information needed to assign weights associated with psychological and sociological elements that inform the decision representation within DYMATICA.
Descriptive and Prescriptive Analytics
DYMATICA is designed to support existing assessment methods by providing greater insight into interactions and influences that can affect the outcome of a situation. These assessments are intended to inform rather than predict precise behaviors by focusing on likely dynamic repercussions of actions—which could help to better understand and compare likely effects of potential COA or actions of other entities under a variety of scenarios.
Typical DYMATICA Assessments
DYMATICA models have assessed different geopolitical and socio-cultural narratives regarding the internal perceptions of a country’s status, capabilities, and hegemony over other countries within a region. This involves the modeling of PMESII-PT factors associated with a country’s economic and military capabilities, as well as their self-perceptions, behavioral tendencies, and internal political dynamics.
For example, the relationship visually described in the figure below might be associated with the question, “How do changes in economic circumstances, military capabilities, geopolitical positioning, and sociopolitical conditions affect a country’s stability and ability to project power over the next ten years?” In this scenario the dynamics within the country can be assessed such as the interactions and influences between political parties, the political leader, as well as other countries that are interacting with the COI.
This assessment would need consider the current and protected economic situation, social and political dynamics, and the narratives that are active within this country. Furthermore, global economic, military, and geopolitical circumstances would also have an impact on the stability within this country. For example, if a more powerful non-NATO neighboring country started to actively use hybrid forms of aggression directed towards a less powerful NATO country, it could have large-scale impacts on the internal social, political, economic stability of that NATO country.
Typical DYMATICA Assessment Outputs
DYMATICA assessments are tailored to fit the information needs of the customer. A DYMATICA assessment might include a number of parameters, such as country GDP which can change over time. These changes can be reflected in the model as parameter updates. For example, economic data updates can come for sources such as the International Monetary Fund or the World Bank. This type of assessment is meant to capture current and near-term conditions.
An analyst can use DYMATICA to better understand various geo-political and sociocultural landscapes if one or more conditions change. To accomplish this, analysts can use the model to adjust parameters to play out various “what if” scenarios. Modifiable parameters can be such things as changes in GDP, levels of military strength in specific areas, degree of aggressiveness in foreign policy, amounts and types of migration, and the like. As one or more of these parameters are adjusted, the results will dynamically change to reflect the scenario change. The visualization of this information is typically presented in a ‘freeware’ platform that is commonly available. This enables the assessments to be widely shared, but also can potentially constrain the richness and flexibility of the assessments to the limitations of that software.
Training Exercise Simulations
DYMATICA is being extended so that it can assess how a combination of socioeconomic, geopolitical, military and environmental conditions, as well as the spreading of information and other societal contagion effects, affect the propensity for an adversary to attack. Also being developed is the ability to assess the resilience of that population and governmental institutions to these attacks.
- DYMATICA has been coupled to a social media model to represent social metadata information and with detailed infrastructure network models to accurately simulate disruptions within a victim country’s infrastructure.
- DYMATICA has been coupled with infrastructure and social media models to develop a hybrid warfare assessment and training system.
In the figure below, three DYMATICA models are coupled with different types of infrastructure models and an agent-based model. Here, the DYMATICA models represent a vulnerable society, including its major institutions and populations (i.e., a victim actor), a country that is supportive to the victim country (i.e., a status-quo actor), including its major institutions and populations, as well as an aggressor country (i.e., a revisionist actor).
- Within the simulated vulnerable society, DYMATICA represents decision making of governmental, banking and media institutions. It also can represent high, medium, and low socio-economic status populations (SES; represented as groups A, B and C in the Figure). This can also include minority groups and their relationships with other minority groups, as well as the majority group and the institutions within that society. Also included in the form of adjustable parameters, are economic conditions, military capabilities, and general resources of the modeled country.
- This was developed by producing a model that represents the decision elements (i.e., perceptions, motivations, intentions, behaviors and the like) for each group and institution entity within each actor. Cue-related information is common to all modeled group and institution entities where each entity will perceive and respond according to their modeled decision calculus, such as their perceptions and motivations.
Modeling the decision calculus of each entity comprises of capturing and representing key decision elements pertinent to those entities and the scenario. These are derived from reports and data with respect to a modeled entity’s perceptions, motivations, norms, and behavioral intentions associated with the scenario. This information is structured in a manner that characterizes both the shorter-term (six hours) and longer-term (such as one or more years) decision processes of institutions and populations. For example, in examining populations, short-term behaviors would be most relevant in responding to infrastructure disruptions. However, governmental institutions would need to respond to both short-term and longer-term disruptions, which would necessitate longer-term goals and policies to remedy the disruptions.
- Addresses how disruptions in such things as electrical power (including Internet communications), foodstuff, petroleum/natural gas, and commuter/ freight rail services affect various populations.
- A semi-fictitious city was developed in order to meet specific training tasks and to keep the scenario at a non-sensitive level. Modeled adversary behaviors are based on actual, but non-attributed behaviors.
For more information
- Bernard, M. L. (2020). Using Computational Geopolitical/Sociocultural Modelling to Assess Response Options to Information-Related Hybrid Threats. Senior Leadership Roundtable on Military and Defense Aspects of Border Security in South East Europe.
- Naugle, A.B., & Bernard, M.L. (2017). Using computational modeling to examine shifts towards extremist behaviors in European diaspora communities. In Advances in Cross-Cultural Decision Making (pp. 321-332). Springer, Cham.
- Passell, H. D., Aamir, M. S., Bernard, M. L., Beyeler, W. E., Fellner, K. M., Hayden, N. K., … & Silver, E. (2016). Integrated human futures modeling in Egypt (No. SAND-2016-0388). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).
Command Authority-Level Decision Making
DYMATICA is being extended to simulate decision making during all phases of combat. Here, well-grounded psychological and behavioral-economic theories and calculations are being used to provide simulated decision making within command authorities down to the tasking of the groups of platforms. Each simulated decision is a function of psychological characteristics along with capability/resource, environmental, and group dynamic factors.
Computationally, the DYMATICA engine consists of a modeling framework and model simulators. The structure allows for model simulation across different domains. This consist of a 1) system representation of dynamic interactions between entities; 2) cognitive model components, which represent the decision process of cognitive entities; and 3) world model components, which include all non-cognitive elements in the simulation (such as adversary positioning, behaviors, and resources). A simplified representation of the DYMATICA decision process is shown in the figure below, which represent the decision making of each simulated command authority.
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