LVC Allocator: Aligning training value with scenario design for envisioned LVC training of fast-jet pilots

Live virtual constructive (LVC) flight simulations mix pilots flying actual aircraft, pilots flying in simulators, and computer-generated forces, in joint scenarios. Training resources invested in LVC scenarios must give a high return, and therefore pilots in both live aircraft and simulators need to experience training value for the extensive resources invested in both, an aspect not emphasized in current LVC research. Thus, there is a need for a function, in this article described as LVC Allocator, which assures that complex LVC training scenarios include aspects of training value for all participants, and, thus, purposefully align scenario design with training value. A series of workshops were carried out with 16 fast-jet pilots articulating the training challenges that LVC could contribute to solving, and allocating LVC entities in a training scenario design exercise. The training values for LVC included large scenarios, weapon delivery, flight safety, adversary performance, and weather dependence. These values guided the reasoning of how to allocate different entities to L, V, or C entities. Allocations were focused on adversaries as V, keeping entity types together, weather dependence, low-altitude and supersonic flying requirements, and to let L entities handle and lead complex tasks to keep the human in the loop.

Modeling the behavior of a hierarchy of command agents with context-based reasoning

Context-based reasoning is a paradigm for modeling agent behavior that is based on the idea that humans only use a small portion of their knowledge at any given time. It was specially designed to represent human tactical behavior and has been successfully implemented in systems with single agents or two agents working together. In this paper, we apply this idea in a hierarchical multi-agent system of command agents, where the agents’ actions are to command and coordinate subordinates, send reports to their superiors, and communicate with other agents at the same level. We focus on how contexts and actions can be defined for these higher level command agents and how the contexts and actions for the different command agents are related. The proposed methodology is implemented and tested for a hierarchy of command agents that are interpreting and planning an operational order at a battalion level and carrying it out in a computer generated forces environment.

Adaptive CGFs Based on Grammatical Evolution

Computer generated forces (CGFs) play blue or red units in military simulations for personnel training and weapon systems evaluation. Traditionally, CGFs are controlled through rule-based scripts, despite the doctrine-driven behavior of CGFs being rigid and predictable. Furthermore, CGFs are often tricked by trainees or fail to adapt to new situations (e.g., changes in battle field or update in weapon systems), and, in most cases, the subject matter experts (SMEs) review and redesign a large amount of CGF scripts for new scenarios or training tasks, which is both challenging and time-consuming. In an effort to overcome these limitations and move toward more true-to-life scenarios, a study using grammatical evolution (GE) to generate adaptive CGFs for air combat simulations has been conducted. Expert knowledge is encoded with modular behavior trees (BTs) for compatibility with the operators in genetic algorithm (GA). GE maps CGFs, represented with BTs to binary strings, and uses GA to evolve CGFs with performance feedback from the simulation. Beyond-visual-range air combat experiments between adaptive CGFs and nonadaptive baseline CGFs have been conducted to observe and study this evolutionary process. The experimental results show that the GE is an efficient framework to generate CGFs in BTs formalism and evolve CGFs via GA.

Research on Armored Mechanized Forces’ Equipment Support Simulation Training System

Armored mechanized forces’ equipment support simulation training system is the use of HLA technology combines emulator, computer generated forces and other devices as a whole which form a virtual battlefield environment in time and space coupling by network. This paper simulation training, introduces the construction of project, establishes the System architecture, and designs the idea which is used in distributed equipment support simulation training system based on the concepts、methods and principles of HLA.