Program Summary
The United States Department of Defense (DoD) and Intelligence Community (IC) need computational systems that can robustly and automatically analyze large amounts of multimodal data. Furthermore, these computational systems need to be able to communicate and cooperate with human beings to resolve ambiguities and improve performance over time.
The Environment-driven Conceptual Learning (ECOLE) program will create artificial intelligence (AI) agents capable of continually learning from language and vision to enable human-machine collaborative analysis of image, video, and multimedia documents during time-sensitive, mission-critical DOD analytic tasks, where reliability and robustness are essential.
ECOLE will transform current ML approaches by developing algorithms that can identify, represent, and ground novel attributes that form the symbolic and contextual model for a particular object or activity through interactive learning with a human analyst.
ECOLE is a 48-month, three-phase program with 18-month Phase 1 and Phase 2 efforts and a 12-month, transition-focused Phase 3 concentrated specifically on development concerns related to GEOINT workflows.