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Scheduling under Uncertainty

Scheduling under Uncertainty. Eugene Fink, Jaime G. Carbonell Ulas Bardak, Alex Carpentier, Steven Gardiner, Andrew Faulring, Blaze Iliev, P. Matthew Jennings, Brandon Rothrock, Mehrbod Sharifi, Konstantin Salomatin, Peter Smatana. Motivation. The available knowledge is uncertain.

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Scheduling under Uncertainty

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  1. Scheduling under Uncertainty Eugene Fink, Jaime G. Carbonell Ulas Bardak, Alex Carpentier, Steven Gardiner,Andrew Faulring, Blaze Iliev, P. Matthew Jennings,Brandon Rothrock, Mehrbod Sharifi,Konstantin Salomatin, Peter Smatana

  2. Motivation The availableknowledge isuncertain • Scheduling under uncertainty • Uncertain resources and scheduling constraints • Search for a schedule with high expected quality We usually make decisions based on incomplete and partially inaccurate info

  3. Demo

  4. Manual and auto scheduling Search time ScheduleQuality ScheduleQuality 0.83 0.83 0.80 0.78 0.72 Auto Auto Auto 0.63 Manual 0.9 Manual Manual 0.8 0.7 0.6 4 1 3 9 2 5 6 7 8 10 13 rooms 84 events 5 rooms 32 events 9 rooms 62 events Time (seconds) 13 rooms 84 events Schedule Size Scheduling results without uncertainty with uncertainty

  5. Info elicitation • Identification of critical missing info • Analysis of trade-offs between its cost and expected schedule improvements Approach • For each candidate question, estimate the probabilities of possible answers • For each possible answer, evaluate its cost and impact on the schedule • For each question, compute its overall expected impact, and select questions with highest positive impacts

  6. Initial schedule: Posters Talk Example: Initial schedule Available rooms: 2 1 3 • Assumptions: • Invited talk: – Needs a projector • Poster session: – Small room is OK – Needs no projector • Events: • Invited talk, 9–10am: Needs a large room • Poster session, 9–11am: Needs a room • Missing info: • Invited talk: – Projector need • Poster session: – Room size – Projector need

  7. Useless info: There are no large rooms w/o a projector × Useless info: There are no unoccupied larger rooms × √ Potentially useful info Example: Choice of questions Initial schedule: 2 1 Posters 3 Talk • Candidate questions: • Invited talk: Needs a projector? • Poster session:Needs a larger room? Needs a projector? • Events: • Invited talk, 9–10am: Needs a large room • Poster session, 9–11am: Needs a room

  8. Initial schedule: 2 1 Posters 3 Talk New schedule: 2 1 3 Talk Example: Improved schedule • Events: • Invited talk, 9–10am: Needs a large room • Poster session, 9–11am: Needs a room Elicitation: System: Does the poster sessionneed a projector? Posters User:A projector may be useful,but not really necessary.

  9. Dependency of the qualityon the number of questions Manual and auto repair ScheduleQuality ScheduleQuality 0.72 0.68 0.72 0.61 Auto withElicitation 0.50 Auto w/oElicitation ManualRepair After Crisis 0.68 10 30 40 50 20 Number of Questions Elicitation results Repairing a conference schedule after a “crisis” loss of rooms.

  10. ScheduleQuality 0.72 with default learning without learning 0.67 20 60 80 100 40 Number of Questions Defaults assumptions Making reasonable assumptions in the absence of specific info • Representation and use • Dynamic learning

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