Human Enemy Network Influence Operations Map (HENIOMAP™)

The HENIOMAP™ technology uses advanced utility-theoretic models to provide a human enemy network influence operations map that incorporates cultural, social, and other factors using a simple knowledge acquisition process. The system assists influence operations (IO) planners in the evaluation and formation of influence operations.

KBSI, in a contract funded by the Office of Naval Research, is developing the hidden enemy network influence operations map (HENIOMAP™) capability, a decision-support tool for course of action (COA) design, analysis and selection in the counterinsurgency (COIN) domain. HENIOMAP™ provides middleware capabilities, assisting COA planners in gap analysis using forward (from COAs to commander's objective) and backward (from commander's objective to COAs) reasoning methods. The HENIOMAP™ COA ontology represents COAs, phases, activities, states, outcomes, measures-of-performance (MOP), and measures-of-effectiveness (MOE). 

This initiative was motivated by recognition of the COIN domain’s complexity and the attendant need to build decision aids that involve the commander and his planning staff as active collaborators.  HENIOMAP™ will take as input the commander’s intent, current situation assessment, COIN options, and knowledge of historical- and situation-defined preferences, and use these inputs to reason to the “critical” gaps where the planner’s creativity should be focused or where more field experience is required. Extensions to the COA ontology can support COIN doctrine, stability operations doctrine, and information operations (IO) doctrine. The use of MOP and MOE to describe outcomes and states, respectively, provides a normalized representation for comparing and analyzing disparate COA elements (states, outcomes, etc.).

With a HENIOMAP™ preference model that represents the trade-offs for resolving conflicting objectives, decision makers can apply gap analysis to:

  • Rank and assess COA plan elements (activities, tasks, states, COA phases and outcomes);

  • identify blind alleys and black holes;

  • validate or challenge assumptions that are implicit in the COA or preference model;

  • validate or modify Human Culture Social Behavior (HSCB) models of the adversary, local population, the "unaligned middle," or other group of interest; and

  • assess information operations (IO) MOP and MOE.

HENIOMAP™ employs a utility-theoretic preference model to compare and analyze COA elements. In this model, a linear utility function is defined over states or outcomes, where the utility function terms are the MOP or MOE that describe the states or outcomes, respectively. Utility theory, as applied to the HENIOMAP™ COIN domain, enables the following capabilities:

  • resolve multiple, conflicting objective;

  • decide among a set of complex alternatives;

  • evaluate trade-offs among multiple objectives; 

  • game and project COA outcomes; and

  • incorporate the perspective of multiple interest groups

The emerging HENIOMAP™ capability will provide support in environments characterized by short decision cycles and incomplete knowledge of both the adversary and the interpretation of the indigenous population of COIN actions.  HENIOMAP™ will be architected to handle situations in which the “complete” plan is not known in advance, supporting re-planning as the situation unfolds.  HENIOMAP™ will serve as an aide and a critic, raising to the forefront the consequences of COA options available to the commander at the decision time, in decision real-time.  In particular, HENIOMAP™ will adapt well even in dynamic IO environments and should dramatically improve missions related to IO and kinetic planning, PSYOP, precision influence targeting, and even strategic communication.

HENIOMAP™ provides the following tangible and practical benefits to COA planners:

  • well-defined MOP and MOE for describing COA plan states and outcomes;

  • MOP and MOE-based metrics for evaluating the progress of the plan as it unfolds;

  • normalization of the effects of an activity, described as changes in state or outcomes, allowing disparate activities and plans to be compared;

  • a catalog of COIN activities defined by the states in which an activity applies, and the expected states that result after application of the activity;

  • a utility-theoretic preference model that represents the trade-offs that a group of interest (blue forces, insurgents, unaligned middle, etc.) makes over conflicting objectives; and

  • the ability to assess COA plan states, activities and outcomes from the perspective of a specific interest group.

Finally, HENIOMAP™ will provide institutional preference knowledge in the form of "leave behind" knowledge products. In the case, for example, of a commander arriving in a new area of responsibility, leveraging the COA lessons learned of the previous leadership can potentially have a very significant impact. HENIOMAP™ mitigates communication and knowledge sharing by delivering preference knowledge products, contextualized to a given culture or geographic area, that the new commander can reference when formulating a fresh COA plan.

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