Human-Machine Collaborative Optimization via Apprenticeship Scheduling

Thesis author Matthew C. Gombolay develops a novel computational technique, Collaborative Optimization Via Apprenticeship Scheduling (COVAS) that enables robots to learn a policy to capture an expert’s knowledge by observing the expert solve scheduling problems. CRICO’s support for his project was through a grant awarded to Neel Shah, MD, of Beth Israel Deaconess Medical Center, and his collaborative work with MIT in finding ways to aid clinicians in making the best OB/Gyn delivery decisions.

Citation for the Full-text Article

Gombolay MC. Human-machine collaborative optimization via apprenticeship scheduling [thesis]. Cambridge, MA: Department of Aeronautics and Astronautics, Massachusetts Institute of Technology; 2017.

Related CRICO Article

Money for Safety: CRICO Pushes Hard to Prevent Medical Harm.