Gamification for Foundations of Prescriptive Analytics CSCI: 2951-O. Serdar Kadıoğlu Dagstuhl Workshop on Planning and Operations Research, 2018

Transcription

1 Gamification for Foundations of Prescriptive Analytics CSCI: 2951-O Serdar Kadıoğlu Dagstuhl Workshop on Planning and Operations Research, 2018

2 CS2951o Topic Domain Application Part I Part II Satisfaction + Optimization + Scalability Intro. to Prescriptive Analytics Boolean Satisfiability DPLL CDCL Constraint Programming Propagation Search Linear Programming Duality Theory Integer Programming Branch & Bound Automative Industry Human Capital Management Supply Chain Management Healthcare Analytics Mass Customization Workforce Scheduling Location Allocation Testcase Diagnosi Part III Local Search / Metaheuristics Transportation Vehicle Routing 2

3 Low-Level High-Level Boolean Satisfiability (SAT) Mathematical Programming (MP) Local Search Metaheuristics (LS) Constraint Programming (CP) 3

4 Inference + Search Interplay of two strategies 1. Representation: How to represent the states? 2. Inference: How to reason about each state? 3. Search: How to select variables/values for branching? 4. Exploration: How to select the next states for expansion? Search Inference Heavily influenced by J. Hooker 4

5 CS2951-O: Foundations of Prescriptive Analytics Instructors: Prof. Uğur Çetintemel & Dr. Serdar Kadıoğlu Teaching Assistants: Tanay Padhi & Isaac Semaya Dept. of Computer Science Spring 2017 Department of Computer Science Brown University 2017

6 1) Projects 5 Projects in total 6

7 2) Narrative Posed as part of business 7

8 2) Continuum of Narrative Supply Chain Management throughout the course Product Configuration (SAT) Workforce Scheduling (CP) Facility Location Customer Allocation (MP) Vehicle Routing (LS, Hybrids) Department of Computer Science Brown

9 3) Leaderboards Results online (Kaggle-like) Building effective solutions is an iterative process Submit solutions anytime Leaderboard updated every 60 seconds Input / Output format is fixed can use any language Immediate feedback on how well your strategy works on instances Track interesting statistics on the back-end Anonymous! Inspired by P. Klein & P. van Brown 9

10 3) Leaderboards Results online (Kaggle-like) 10

11 3) Leaderboards Results online (Kaggle-like) 11

12 4) Collaboration Build Together Software is build in teams (for good or bad!) Collaboration is mandatory Cannot partner with the same person all semester Different partner in 3/5 projects Inspired by M. Sellmann 12

13 5) Communication Multiple Personas 1. Reports Each project accompanied with a report a) Developer Heavy implementation details b) Modeler How to formulate, alternatives? c) Business owner Would this really work, what s missing? 2. Post-mortem In-class discussion led by students 3. Final Presentation Open to department 13

14 Some Observations Things learned Gathering fun instances is not easy A lot of improvements initially, progress slows down, stops eventually Mental barrier? Once one student solves the puzzle, improvements follow Grading is not easy, solutions converge 14

15 Initial Feedback Gamification helps 15

16 Initial Feedback Gamification helps 16

17 Initial Feedback Gamification helps 17

18 Initial Feedback Gamification helps 18