Automated Planner for a Field-Service Maintenance Schedule
Overview
What this challenge is about.
Model a field-service schedule as a PDDL or CSP solver, evaluate against real data, and deliver a repo with report to earn your verifiable certificate.
The scenario
The Toronto facilities-management company (around CAD 65M revenue, mid-market commercial buildings) has a planner who's 5 years from retirement — the AI planner is a succession-risk hedge, not a cost play.
The Brief
What you'll do, and what you'll demonstrate.
Build a classical-AI planner for preventive-maintenance scheduling that matches or beats the human planner on visit-coverage + drive-time efficiency.
Earning criteria — what you'll demonstrate
- Apply classical AI planning (PDDL or CSP) to a real scheduling problem
- Design an encoding that captures domain constraints faithfully
- Evaluate AI planners against human-decision baselines defensibly
- Recommend ship/don't-ship with trade-off honesty
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Introduction to Artificial Intelligence (CS Elective)
Bachelor · General Studies
Strong alignment
This challenge maps to Introduction to Artificial Intelligence (CS Elective) at the Bachelor level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Planning
Apply planning to solve real industry problems and demonstrate production-level capability.
- Constraint Satisfaction
Apply constraint satisfaction to solve real industry problems and demonstrate production-level capability.
- Python Programming
Apply python programming to solve real industry problems and demonstrate production-level capability.
- Algorithm Evaluation
Apply algorithm evaluation to solve real industry problems and demonstrate production-level capability.
- Intelligent Agents
Apply intelligent agents to solve real industry problems and demonstrate production-level capability.
- Optimization
Apply optimization to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
PMs on field-ops and logistics products need this planner fluency to scope automation that respects real-world constraint complexity.
This challenge sharpens
- planning
- algorithm-evaluation
- intelligent-agents