Virtual Observer Controllers for Adaptive Training (VOCAT)

This proposal describes how adaptive training for tactical decision making can be obtained through the use of Virtual Observer/Controllers (VO/C), which shall be developed to mimic human observer/controllers (O/Cs). Our objective in this proposal is to use our patented reflection technology to model VO/Cs that can perform the jobs of a human O/C for an Anti-Submarine Warfare Evaluator (ASWE), thus developing an adaptive training solution for ASW that effectively and efficiently individualizes training for trainees by identifying non-optimal instances of state and/or performance, identifying the root cause(s) of issues, mitigating root cause(s) of issues in an appropriate manner, and summarizing trainee status post-scenario via a comprehensive, targeted AAR. The end result is a training system that helps to enable realistic training. Although our approach shall be general, the proposed effort shall focus on the needs of our HIFAST transition partner, with initial focus on the ASWE. The ASWE is critical to operations and targeted for early transition of training. The proposed Virtual Observer Controllers for Adaptive Training (VOCAT) shall leverage work from past efforts in creating domain specific consoles to support instructors in training. We focus on the capture of expertise from instructors and the design of the VOCAT console.