Overview
What this challenge is about.
You encode smart-grid curtailment as a SAT problem and compare against a greedy heuristic to earn a verifiable certificate.
The scenario
The startup (around 70 staff) bids aggregated curtailment into the German balancing market and lives on event-response quality; a 10 percent improvement is worth around EUR 700k annual revenue.
The Brief
What you'll do, and what you'll demonstrate.
Decide whether a SAT/MaxSAT planner beats the greedy heuristic on curtailment delivered within a 60-second dispatch budget.
Earning criteria — what you'll demonstrate
- Encode a real planning problem as SAT/MaxSAT
- Use an off-the-shelf solver under a strict time budget
- Compare against an industry baseline with realistic event data
- Reason about production integration of a SAT-based component
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Automated Planning
Master · Ai Systems
Strong alignment
This challenge maps to Automated Planning at the Master 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.
- Sat Based Planning
Apply sat based planning to solve real industry problems and demonstrate production-level capability.
- Constraint Encoding
Apply constraint encoding to solve real industry problems and demonstrate production-level capability.
- Benchmarking
Apply benchmarking to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Domain Modeling
Apply domain modeling to solve real industry problems and demonstrate production-level capability.
- Experiment Design
Apply experiment design 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:
ML Researcher
Rigorous benchmarking of a SAT-based method against a production heuristic is exactly the experimental discipline ML researchers practice.
This challenge sharpens
- sat-based-planning
- benchmarking
- experiment-design
AI Engineer
SAT encoding on a real ops problem with a production-integration sketch is high-value AI engineering work in grid + supply-chain startups.
This challenge sharpens
- constraint-encoding
- domain-modeling
- sat-based-planning
Applied AI Scientist
Turning a solver experiment into a memo with revenue framing is what applied AI scientists do at infrastructure-AI companies.
This challenge sharpens
- benchmarking
- experiment-design
- domain-modeling