minimal retentive sets in tournaments
play

Minimal Retentive Sets in Tournaments From Anywhere to TEQ Felix - PowerPoint PPT Presentation

Minimal Retentive Sets in Tournaments From Anywhere to TEQ Felix Brandt Markus Brill Felix Fischer Paul Harrenstein Ludwig-Maximilians-Universitt Mnchen Estoril, April 12, 2010 1 / 17 The Trouble with Tournaments Tournaments


  1. Minimal Retentive Sets in Tournaments – From Anywhere to TEQ – Felix Brandt Markus Brill Felix Fischer Paul Harrenstein Ludwig-Maximilians-Universität München Estoril, April 12, 2010 1 / 17

  2. The Trouble with Tournaments Tournaments are oriented complete graphs Many applications: social choice theory, sports tournaments, game theory, argumentation theory, webpage and journal ranking, etc. Question: How to select the winner(s) of a tournament in the absence of transitivity? a c b e d 2 / 17

  3. The Trouble with Tournaments Tournaments are oriented complete graphs Many applications: social choice theory, sports tournaments, game theory, argumentation theory, webpage and journal ranking, etc. Question: How to select the winner(s) of a tournament in the absence of transitivity? a c b e d 2 / 17

  4. Overview Tournament solutions Retentiveness and Schwartz’s Tournament Equilibrium Set (TEQ) Properties of minimal retentive sets ‘Approximating’ TEQ A new tournament solution 3 / 17

  5. Tournament Solutions a c b A tournament T = ( A , ≻ ) consists of: • a finite set A of alternatives • a complete and asymmetric relation ≻ on A e d 4 / 17

  6. Tournament Solutions a c b A tournament T = ( A , ≻ ) consists of: • a finite set A of alternatives • a complete and asymmetric relation ≻ on A e d A tournament solution S maps each tournament T = ( A , ≻ ) to a set S ( T ) such that ∅ � S ( T ) ⊆ A and S ( T ) contains the Condorcet winner if it exists • S is called proper if a Condordet winner is always selected as only alternative 4 / 17

  7. Tournament Solutions a c b A tournament T = ( A , ≻ ) consists of: • a finite set A of alternatives • a complete and asymmetric relation ≻ on A e d A tournament solution S maps each tournament T = ( A , ≻ ) to a set S ( T ) such that ∅ � S ( T ) ⊆ A and S ( T ) contains the Condorcet winner if it exists • S is called proper if a Condordet winner is always selected as only alternative Examples: Trivial Solution (TRIV), Top Cycle (TC), Uncovered Set, Slater Set, Copeland Set, Banks Set, Minimal Covering Set (MC), Tournament Equilibrium Set (TEQ) , . . . 4 / 17

  8. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) a b 5 / 17

  9. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) a b 5 / 17

  10. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) a b 5 / 17

  11. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) a b 5 / 17

  12. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  13. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  14. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  15. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  16. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  17. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  18. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  19. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) 5 / 17

  20. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b a 5 / 17

  21. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b a 5 / 17

  22. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b a 5 / 17

  23. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b a 5 / 17

  24. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b a 5 / 17

  25. Basic Properties of Tournament Solutions Monotonicity (MON) Weak Superset Property (WSP) Strong Superset Property (SSP) Independence of Unchosen Alternatives (IUA) b Note: a SSP is equivalent to ˆ α (see Felix’s lecture) (SSP ∧ MON) implies WSP and IUA 5 / 17

  26. Examples Definition: TRIV returns the set A for each tournament T = ( A , ≻ ) 6 / 17

  27. Examples Definition: TRIV returns the set A for each tournament T = ( A , ≻ ) Definition: TC returns the smallest dominating set , i.e. the smallest set B ⊆ A with B ≻ A \ B • Intuition: No winner should be dominated by a loser 6 / 17

  28. Examples Definition: TRIV returns the set A for each tournament T = ( A , ≻ ) Definition: TC returns the smallest dominating set , i.e. the smallest set B ⊆ A with B ≻ A \ B • Intuition: No winner should be dominated by a loser B A \ B 6 / 17

  29. Examples Definition: TRIV returns the set A for each tournament T = ( A , ≻ ) Definition: TC returns the smallest dominating set , i.e. the smallest set B ⊆ A with B ≻ A \ B • Intuition: No winner should be dominated by a loser • Define D ( b ) = { a ∈ A : a ≻ b } • TC is the smallest set B satisfying D ( b ) ⊆ B for all b ∈ B B D ( b ) b A \ B B 6 / 17

  30. Examples Definition: TRIV returns the set A for each tournament T = ( A , ≻ ) Definition: TC returns the smallest dominating set , i.e. the smallest set B ⊆ A with B ≻ A \ B • Intuition: No winner should be dominated by a loser • Define D ( b ) = { a ∈ A : a ≻ b } • TC is the smallest set B satisfying D ( b ) ⊆ B for all b ∈ B Both TRIV and TC satisfy all four basic properties B D ( b ) b A \ B B 6 / 17

  31. Retentiveness Intuition: • An alternative a is only “properly” dominated by a “good” alternatives Thomas Schwartz 7 / 17

  32. Retentiveness Intuition: • An alternative a is only “properly” dominated by a “good” alternatives, i.e., alternatives selected by S from the dominators of a Thomas Schwartz 7 / 17

  33. Retentiveness Intuition: • An alternative a is only “properly” dominated by a “good” alternatives, i.e., alternatives selected by S from the dominators of a • No winner should be “properly” dominated by a loser Thomas Schwartz 7 / 17

  34. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) Thomas Schwartz b B 7 / 17

  35. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) D ( b ) Thomas Schwartz b B 7 / 17

  36. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) D ( b ) S ( D ( b )) Thomas Schwartz b B 7 / 17

  37. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) D ( b ) S ( D ( b )) Thomas Schwartz b B ˚ Definition: S returns the union of all minimal S -retentive sets 7 / 17

  38. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) D ( b ) S ( D ( b )) Thomas Schwartz b B ˚ Definition: S returns the union of all minimal S -retentive sets • Call ˚ S unique if there always exists a unique minimal S -retentive set 7 / 17

  39. Retentiveness B is S-retentive if B � ∅ and S ( D ( b )) ⊆ B for Definition: all b ∈ B D ( b ) D ( b ) S ( D ( b )) Thomas Schwartz b B ˚ Definition: S returns the union of all minimal S -retentive sets • Call ˚ S unique if there always exists a unique minimal S -retentive set • Minimal S -retentive sets exist for each tournament • ˚ S is unique if and only if there do not exist two disjoint S -retentive sets 7 / 17

  40. Example ˚ Proposition: TRIV = TC 8 / 17

  41. Example ˚ Proposition: TRIV = TC Proof: A set is TRIV -retentive if and only if it is dominating D ( b ) TRIV ( D ( b )) = D ( b ) b B 8 / 17

  42. The Tournament Equilibrium Set ˚ The tournament equilibrium set (TEQ) is defined recursively as TEQ = TEQ 9 / 17

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend