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Pnyx A user-friendly tool for preference aggregation.
An IDP by Guillaume Chabin guillaume.chabin@tum.de
Agenda ① Mo;va;ons
② Pnyx features ③ Pnyx & Social Choice Theory ④ What lies behind Pnyx?
⑤ Future works
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 2
How do we perform a preference aggregation?
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 3
We have several possible tools
But none of these are built for polls!
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 4
No user-friendly solution to collect and aggregate preferences
Niche : Marke;ng
tools
Aggrega;on tools
Collec;on tools
?
Complete
Incomplete
Niche : Social vo;ng User oriented Code oriented
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 5
Niche : Elec;on tools
No user-friendly solution to collect and aggregate preferences
Complete
Incomplete
User oriented Code oriented
6
Niche : Marke<ng tools
Niche tools: Social vo<ng
Collec<on tool Aggrega<on toll
Pnyx •
Doodle •
• myVote
• Show of hands • voIer
• wedgies
• Helios
• polarb
Survey Monkey •
• Limesurvey
• tricider
• CIVS • Simply Vo<ng
• OpaVote • ballotbin.com
Qualtrics •
• democrtarix
Niche : Elec<on tools
Pnyx aims to address this need. • Open source & user-‐friendly • A unique tool from the collec;on to the
preference aggrega;on
With Pnyx
With other aggrega;on tools
Extract preference profile under Preflib’s standards
Collect pref. Build pref. profile (external tool)
Aggregate profile
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 7
How do we use Pnyx?
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 8
General information Pnyx is a web-‐based applica<on • Currently deployed on a TUM server • pnyx.dss.in.tum.de User data required: • 2 different type of users:
admin and voters • Pnyx account required for admins • Voter’s email address required (only for
private polls)
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 9
Admin features: Create a poll:
• Create a poll and invite par;cipants Manage exis<ng polls:
• Contact par;cipants • Modify or delete a poll • Export a preference profile
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 10
Poll creation
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Poll creation (2)
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Poll creation (3)
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Poll creation (4)
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Poll creation (5)
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Poll creation (6)
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Voter features No registra;on required
Public or individual links
2 major func;onali;es
• Access the ballot and vote • See the (temporary) results
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 17
Voter features (2)
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 18
Voter features (3)
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 19
What if a voter tries to trick Pnyx?
Pnyx uses redirec<ons:
• Timeframe viola;on • Access a private poll
without being a par;cipant • Vote twice • …
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 20
Features around Pnyx
Features related to the account management
About page & contact us
User Interface to interact with the database
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 21
Pnyx and SCT
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 22
Individual preferences Pnyx supports 5 different restricted domains for individual preferences
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 23
Collective preferences 3 different output types to aggregate preference profiles
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 24
Selection of the choice rule according a matrix
* Plurality Approval vo<ng
Borda’s score
Bucket Borda’s score
Young’s scoring rule
Random Dictatorship
Nash solu<on ∆
Maximal LoIery ∆
Maximal LoIery ∆
Maximal LoIery ∆
Plurality score *
Approval score *
Kemeny’s rule ∆
Kemeny’s rule ∆
Kemeny’s rule ∆
* <e breaking according a customized or randomized lexicographic order ∆ uncontrolled <ebreak
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 25
Nash’s solution From Collec.ve choice under dichotomous preferences, A. Bogomolnaia, H. Moulin and R. Stong Maximize a collec<ve u<lity func<on Solved by convex op;miza;on:
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 26
Nash’s solution (ctd.) Meets ex-‐ante efficiency : Meets fair welfare share: • Guarantees a lower bound on the u;lity
of all agents who are not completely indifferent.
Not strategyproof (impossibility result)
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 27
Maximal lottery Expected majority margin:
ML set is a convex polytope and may be large:
• The .ebreak = get closer to the center of gravity
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 28
Maximal lottery ML are mixed maximin strategies of the plurality game • Compute some ver;ces with LP:
• Take the average
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 29
Maximal lottery (2) No generaliza<on for loIery outcomes: • ML are Condorcet extensions and not the
others • Nash’s solu;on more sensi;ve to voters
with a low u;lity
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 30
4 3 2
A D B
B,C,D A,B,C A,C,D 44,4
33,6
100
22,2
32,9
33,3
33,4
0% 20% 40% 60% 80% 100%
Ran Dic
Nash Sol.
Max Lot
A B D
Kemeny’s rule Kemeny’s rule is NP–complete
Computed by MIP
A B
C D
1
3
1
1 1 1
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 31
A B
C D
1
3
1
1
1
1
0
0 0
0
0
0
Kemeny’s rule (2) Generaliza<on among ranking outcomes:
In theory
• Rm is transi;ve on Ddi
In prac;ce
• The ;ebreaking rule is not controlled for Kemeny’s rule implementa;on
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What lies behind Pnyx?
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Lp solver: GLPK
Backen
d
Web framework
Django
Python package
Fron
tend
Data base
jQuery JavaScript library
Bootstrap HTML & CSS-‐based design templates
Template layer
View layer
Model layer
others Numpy cvxopt puLP
A global picture of Pnyx
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 34
Next steps? Technical topics
Improve the database interface
Fixe some remaining bugs
• Remaining ;ebreaking rules support Improve Pnyx for mobile
• Design with Bootstrap • Op;mized ballots for mobile
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 35
Next steps? Theatrical topics
Improve the trus<ness of Pnyx
• Op;mize the data base • Encrypt ballots and results
Other topics related to collec<ve preferences
• Implement matching…
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 36
Conclusion • Developed a func;onal app from
scratch • Learned a lot about web development • Nice tool to introduce Social Choice
Theory around me • I hope Pnyx will have a dynamic and
bright future
August 20, 2014
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 37
Thank you for your attention August 20, 2014 38
Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de
Cred
its • Problem Solving designed by Rob Maslin from the Noun Project
• Collect designed by Icons8 from the Noun Project
• Thinking designed by Jens Tärning from the Noun Project
• Server designed by aLf from the Noun Project
• Internet designed by Cindy Hu from the Noun Project
• Floppy Disk designed by Cor Tiemens from the Noun Project
• Administrator designed by Dungeon Hero X from the Noun Project
• User designed by Wilson Joseph from the Noun Project
• Update Profile designed by gonzalo garrido from the Noun Project
• Informa;on designed by José Campos from the Noun Project
• Database designed by Shmidt Sergey from the Noun Project
• Thief designed by André Renault from the Noun Project
• Fast Forward designed by aguycalledgary from the Noun Project
• Ques;on designed by Mar;n Delin from the Noun Project
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Why those choices? Python
• Programming language • Support web & scien;fic programming • Implementa;on of all the applica;on logic
Django • Web app framework in python • Lots of built-‐in func;onali;es • Easy to grasp
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Pnyx: IDP final presena;on -‐ guillaume.chabin@tum.de 40
Why those choices? (ctd) Bootstrap
• HTML & CSS template design • Nice design without huge • Theme from bootswatch.com
jQuery • Required for bootstrap • Standard JavaScript libraries • Nice built-‐in features for UI
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