Stokes, Devvan
Synthetic Adversaries for Urban Combat Training
Wray, Robert E., Laird, John E., Nuxoll, Andrew, Stokes, Devvan, Kerfoot, Alex
This article describes requirements for synthetic adversaries for urban combat training and a prototype application, MOUTBots. MOUTBots use a commercial computer game to define, implement, and test basic behavior representation requirements and the Soar architecture as the engine for knowledge representation and execution. The article describes how these components aided the development of the prototype and presents an initial evaluation against competence, taskability, fidelity, variability, transparency, and efficiency requirements.
Synthetic Adversaries for Urban Combat Training
Wray, Robert E., Laird, John E., Nuxoll, Andrew, Stokes, Devvan, Kerfoot, Alex
Six high-level requirements drive the implementation of intelligent synthetic adversaries for training: (1) competence, (2) taskability, (3) observational fidelity, (4) behavior variability, most difficult tasks soldiers perform. Frequent Competence: The adversaries must perform training is an essential element in reducing the tactics and missions humans perform in casualties. For this application, the adversaries' environments is costly and restricted to physical goal is to defend a small multistoried mockups of buildings and small towns. The agents must move Environments (VIRTE) program is developing immersive virtual trainers for military operations through the environment, identify tactically on urbanized terrain (MOUT). In this relevant features (such as escape routes), and trainer, four-person fire teams of U.S. Marines communicate and coordinate with other are situated in a virtual urban environment and agents. Virtual opponents new missions for different training scenarios, are required to populate the environment and and they must change their objectives challenge the trainees.