#1 Accelerated Learning through Advanced Neural Interfaces
Noninvasive neural interface technologies that can reduce training time, increase learning, and enable more rapid, effective decision making.
Seeking noninvasive brain machine/brain computer interface technologies/general advances that effectively interface the nervous system technologies. This can include hardware (e.g. optical, electrical, magnetic-based, acoustic-based) or software (e.g. advanced signal processing algorithms, machine learning). We are especially interested in, but not limited to technologies that provide alternative inputs into augmented, virtual, and/or mixed reality and nervous system-based technologies that can enable more rapid, effective decision making.
#2 Supporting a Sustainable Training Ecosystem
Technology to improve the speed and quality of decisions, and training technology to improve how effectively we adapt to rapidly changing situations – particularly in a complex, dynamic, and uncertain operating environment.
Seeking training technologies to create an ecosystem that supports real time reconfiguration & adaptation as new capabilities emerge where sophisticated autonomous systems and human operators can interact and train as teams in operationally relevant environments. This might include:
- Managing learning events and developing prediction models of trajectories for future events
- Automated scenario content metadata tagging
- Intelligent tutoring mechanisms to support adaptive operational training and exercises
- Rapid instructor and student modeling from existing learning environment data
- Methods for less obtrusive learner monitoring and content adaptation