The Design of a User-Centric Scheduling System for Multifaceted Real-World Problems
Pauline M. Berry, Michael D. Moffitt, Bart Peintner, Neil Yorke‐Smith · 2007
A chief hindrance to the practical value of AI scheduling and planning tools stems from the difficulty in adequately encod-ing domain knowledge. Using imperfect domain knowledge, fully automated systems that abstract away the ‘scruffy ’ real world tend to produce fragile schedules that omit important constraints and optimize artificial metrics. As a result, these systems are ultimately often rejected by the user. We de-scribe the design of a user-centric scheduling system, Pisces, that assists the user in exploring the rich space of schedules in complex, real-world domains with multifaceted objectives. Pisces retains the strength of humans in understanding sched-ule quality and nuances of domain constraints, while leverag-ing the power and flexibility of constraint-based scheduling algorithms. The system helps the user to iteratively craft a so-lution by expressing both high-level guidance and low-level specific constraints and preferences.