1. Introduction to Network Mathematics (3) - Simple Games and applications Yuedong Xu 16/05/2012

2. Outline Overview Prison’s Dilemma Curnot Duopoly Selfish Routing Summary

3. Overview What is “game theory”? – A scientific way to depict the rational behaviors in interactive situations – Examples: playing poker, chess; setting price; announcing wars; and numerous commercial strategies Why is “game theory” important? – Facilitates strategic thinking!

4. Overview Olympic Badminton Match 2012 – Four pair of players expelled because they “throw” the matches – Why are players trying to lose the match in the round-robin stage?

5. Overview Chinese VS Korean – If Chinese team wins, it may encounter another Chinese team earlier in the elimination tournament. (not optimal for China) Best strategy for Chinese team: LOSE – If Korean team wins luckily, it may meet with another Chinese team that is usually stronger than itself in the elimination tournament. Best strategy for Korean team: LOSE

6. Overview Korean VS Indonesian – Conditioned on the result: China Lose – If Korean team wins, meet with another Korean team early in the elimination tournament. (not optimal for Korea) Best strategy for Korean team: LOSE – If Indonesian wins, meet with a strong Chinese team in the elimination tournament. Best strategy for Indonesian team: LOSE

7. Overview What is “outcome”? – Ugly matches that both players and watchers are unhappy – By studying this case, we know how to design a good “rule” so as to avoid “throwing” matches

8. Outline Overview Prison’s Dilemma Curnot Duopoly Selfish Routing Summary

9. Prison’s Dilemma Two suspects are caught and put in different rooms (no communication). They are offered the following deal: – If both of you confess, you will both get 5 years in prison (-5 payoff) – If one of you confesses whereas the other does not confess, you will get 0 (0 payoff) and 10 (-10 payoff) years in prison respectively. – If neither of you confess, you both will get 2 years in prison (-2 payoff)

10. Prison’s Dilemma Prisoner 2 Prisoner 1 Confess Don’t Confess Confess -5, -50, -10 Don’t Confess -10, 0-2, -2

11. Prison’s Dilemma Prisoner 2 Prisoner 1 Confess Don’t Confess Confess -5, -50, -10 Don’t Confess -10, 0-2, -2

12. Prison’s Dilemma Game – Players (e.g. prisoner 1&2) – Strategy (e.g. confess or defect) – Payoff (e.g. years spent in the prison) Nash Equilibrium (NE) – In equilibrium, neither player can unilaterally change his/her strategy to improve his/her payoff, given the strategies of other players.

13. Prison’s Dilemma Some common concerns – Existence/uniqueness of NE – Convergence to NE – Playing games sequentially or repeatedly More advanced games – Playing game with partial information – Evolutionary behavior – Algorithmic aspects – and more ……

14. Prison’s Dilemma – Two NEs Prisoner 2 Prisoner 1 Confess Don’t Confess Confess -5, -5-3, -10 Don’t Confess -10, -3-2, -2

15. Prison’s Dilemma – No NE Rock-Paper-Scissors game: If there exists a NE, then it is simple to play!

16. Outline Overview Prison’s Dilemma Curnot Duopoly Selfish Routing Summary

17. Curnot Duopoly Basic setting: Two firms: A & B are profit seekers Strategy: quantity that they produce Market price p: p = 100 - (q A + q B ) Question: optimal quantity for A&B

18. Curnot Duopoly A’s profit: Strategy: quantity that they produce Market price p: p = 100 - (q A + q B ) Question: optimal quantity for A&B

19. Curnot Duopoly A’s profit: π A (q A,q B ) = q A p = q A (100-q A -q B ) B’s profit: π B (q A,q B ) = q B p = q B (100-q A -q B ) How to find the NE?

20. Curnot Duopoly A’s best strategy: dπ A (q A,q B ) —————— = 100 - 2q A – q B = 0 dq A B’s best strategy: dπ B (q A,q B ) —————— = 100 - 2q B – q A = 0 dq B Combined together: q A * = q B * = 100/3

21. Curnot Duopoly Take-home messages: – If the strategy is continuous, e.g. production quantity or price, you can find the best response for each player, and then find the fixed point(s) for these best response equations.

22. Outline Overview Prison’s Dilemma Curnot Duopoly Selfish Routing Summary

23. Selfish Routing Braess’s Paradox st x1 x 1 0 st x1 x 1 Traffic of 1 unit/sec needs to be routed from s to t Want to minimize average delay Braess 1968, in study of road traffic

24. Selfish Routing Before and after st x1 1 x 1 0 0 1 0 1 st x1.5 x 1 Think of green flow – it has no incentive to deviate Adding a 0 cost link made average delay worse!!!

25. Selfish Routing Braess’s paradox illustrates non- optimality of selfish routing Think of the flow consisting of tiny “packets” Each chooses the lowest latency route This would reach an equilibrium (pointed out by Wardrop) – Wardrop equilibrium = Nash equilibrium

26. Summary Present the concept of game and Nash Equilibrium Present a discrete and a continuous examples Illustrate the selfish routing

27. Thanks!