1 / 42

Information, Control and Games

Information, Control and Games. Shi-Chung Chang EE-II 245, Tel: 2363-5251 ext. 245 scchang@cc.ee.ntu.edu.tw, http://recipe.ee.ntu.edu.tw/scc.htm Office Hours: Mon/Wed 1:00-2:00 pm or by appointment Yi-Nung Yang (03 ) 2655201 ext. 5205, yinung@cycu.edu.tw.

aggie
Download Presentation

Information, Control and Games

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Information, Control and Games Shi-Chung Chang EE-II 245, Tel: 2363-5251 ext. 245 scchang@cc.ee.ntu.edu.tw, http://recipe.ee.ntu.edu.tw/scc.htm Office Hours: Mon/Wed 1:00-2:00 pm or by appointment Yi-Nung Yang (03 ) 2655201 ext. 5205, yinung@cycu.edu.tw

  2. Normal Form (one-shot) games. Solution concepts: the Nash Equilibrium. Lecture 2

  3. What is a game? • A finite set N of players • N = { 1, 2, …. , i , ……n} • A set of strategies Si for each player • Strategies (actions ) set • Si = { si : si is a strategy available to player i } Si may be finite or infinite. • A payoff function i for each player. • iassigns a payoff to player i depending on which strategies the players have chosen.

  4. Example 1 • Working on a joint project • 兩人合作寫 term project • Both work hard: • One works hard but the other goofs off • Both goof off

  5. Example 1 (cont.) • Working on a joint project: • A finite set N of players • N = { 1, 2} • A set of strategies Si for each player • Strategies (actions ) set • Si = { work hard, goof off} • A payoff function i for each player. • 1(W, W)= 2 = 2(W,W) • 1(W, G)= 0 = 2(G,W) • 1(G, W)= 3 = 2(W,G) • 1(G, G)= 1 = 2(G,G)

  6. Example 1 (cont.) • Normal Form

  7. Example 2 • Duopoly • 價格戰: 中油 vs 台塑

  8. Example 3 • Coordination gameBattle of the Sexes (BoS) • 合則兩利, 不合則兩害

  9. Solution to The famous Prisoner’s Dilemma • Prisoner’s Dilemma—an engineer’s version • Suppose each of two engineers wants to build a bridge or a tunnel across the Amazon from city A to city B. • It costs $20 million to build a bridge and $50 million to build a tunnel. • Revenue • If both build a bridge/tunnel, each can sell her bridge/tunnel for $80 million. • if one builds a bridge and one builds a tunnel, the bridge will sell for $25 million and the tunnel will sell for $120 million • Why? Due to high winds and heavy rains in the area, most people when given a choice will choose to drive through a tunnel.

  10. Player 2 bridge tunnel bridge 60, 60 5, 70 Player 1 tunnel 70, 5 30, 30 N = {1, 2} S1 = {bridge, tunnel} = S2 I (bridge, bridge) = 80-20=60= 2 (bridge, bridge) I (tunnel, tunnel) = 80-50=30= 2 (tunnel, tunnel) I (bridge, tunnel) = 25-20=5= 2 (tunnel, bridge) I (tunnel, bridge) = 120-50=70= 2 (bridge, tunnel)x Bimatrix Form: 10

  11. Solution Concepts • What is a solution to a game? • We want a solution to predict what strategies players will choose. • Note: solutions can also be prescriptive—they can tell us what strategies players should play. • We will concentrate for now on the predictive performance of a solution. • We can test a solution’s predictive ability experimentally, by having subjects (often students) play games in a laboratory or empirically, by seeing how firms behave in a market, or how politicians behave in an election.

  12. The Premier solution concept: The Nash Equilibrium • We will use the PD game to introduce the concept. • Why is this the premier concept in game theory? • Because it has performed relatively well in experimental tests and empirical tests and is widely applicable. (See Osborne’s discussion p.25).

  13. Let’s look back at our bimatrix form of Prisoner’s Dilemma. • Our two engineers see the 60, 60 payoff and would like to agree to build bridges. • However, even if they meet to talk things over and agree--- Engineer 1 will Reason as follows: If 2 builds a bridge I can earn 60 or defect to a tunnel and earn 70. And if 2 cheats and builds a tunnel, I will earn 5 or defect and earn 30. • So no matter what 2 does I do better building a tunnel!!! • Therefore I build a tunnel • Player I reasons similarly and builds a tunnel. Each earns 30.

  14. We have two solution concepts so far • Players agree to jointly “optimize”: (bridge, bridge)this is also called a Pareto optimal outcome • Dominant strategy equilibrium: (tunnel, tunnel) • Why would we predict that the dominant strategy will be played and not the joint optimal solution? • The logic to playing the dominant strategy equilibrium is overwhelming. I earn more with tunnel no matter what my opponent does. • Moreover, dominant strategy equilibrium tests well in experiments in the lab even in Prisoner’s Dilemma (see Osborne’s discussion). • All sorts of examples too. OPEC, anti-trust cases (firms found to have cheated on price agreements, avoidance of PD etc)..

  15. Pareto Optimal Outcome? • When will the players play the joint optimal solution? • When it is possible for players to form legal binding commitments. For example, write a legal contract. • Conclusion: • On the day of the press conference the two engineers announce what each will build. • They may have agreed before hand to build bridges. • But they will both announce: TUNNEL • Unless they were able to write an enforceable contract. • Not so easy to do in most situations and often illegal. • Firms have to make their way around Prisoner’s Dilemma!

  16. Comments: • 1. We are discussing noncooperativegame theory where no binding contracts are • allowed. • We are discussing one-shot simultaneous play games where both players must • announce their strategies simultaneously and the game is played once. • We have seen an example of a dominant strategy equilibrium. Here’s the • definition for a two player game. • A dominant strategy equilibrium is a strategy pair (s1*, s2*) such that s1*  S1, • s2*  S2 , • I (s1*, s2) > I (s1, s2) for all s1 S1, s2 S2 ,and s1 not equal to s1* • 2 (s1, s2*) > 2(s1, s2) for all s1 S1, s2 S2 ,and s2 not equal to s2*. • Most games don’t have dominant strategy equilibrium. That’s why Nash • introduced the Nash equilibrium, which generalizes the dominant strategy • equilibrium with which it shares its defining characteristic, stability.

  17. Definition • A Nash equilibrium is an strategy profile s* with the property that no player i can do better by choosing and action different from si*, given that every other player j adheres to sj*s* = {si*, sj*}

  18. Now let’s define a Nash equilibrium. We will look at a game that has a Nash equilibrium, but no dominant strategy Equilibrium. Here are four equivalent definitions of a Nashequilibrium. First two give us a feeling for what a Nash equilibrium is. The second two are useful for funding the Nash equilibrium or equilibria for a specific game.

  19. Given a game G = (N = {1,2}; S1, S2 ; I, 2), the strategy pair (s1*, s2*) is a Nash equilibrium for G if 1.Neither player has an incentive to unilaterally defect to another strategy. 2. s1* is a best response to s2*and s2*is a best response to s1*. 3. 1 (s1*, s2*)  1 (s1, s2*) for all s1 S1. and 2 (s1*, s2*)  2 (s1*, s2) for all s2 S2. 4. I (s1*, s2*) is a column maximum and 2 (s1*, s2*) is a row maximum.

  20. Uniqueness of Nash equil. • If a Nash equil. exist, is it unique? • Example: Battle of the sexes • It is a Saturday night, Geroge loves to watch football, but Marry enjoys opera.... • They also like each other’s company... • Find the Nsah equil.?

  21. Existence of Nash equilibrium • Same as before with a slight modification • George wants to meet Marry. However, Marry wants to avoid George • The only activities are a movie and a dance • Marry prefers to be alone, but if she must be with George, she prefers the movie, since she won’t have to talk to George. • George prefers to be with Marry, and if he succeeds, he prefers the dance, where he can talk to her. • Find Nash eq.

  22. Exercise: A Sealed Bid Auction. Suppose two bidders bid for an item they know they can sell for $20. The rules of the auction require a bid of $16, $10, or $4. If both bidders submit the same bid, they share the item. Put the game in normal form.

  23. 2 H M L 2,2 4,0 4,0 H 0,4 5,5 10, 0 1 M 0,4 0, 10 8,8 L

  24. 1. Is there a dominant strategy equilibrium? • What is player 1’s best response to H? • What is player 1’s best response to M? • What is player 1’s best response to L? • So no one strategy of player 1 is a best response to all strategies of player 2. • Find all Nash equilibria. • Is (H,H) a Nash equilibrium? • Is (H,M) a Nash equilibrium? • etc. • Note a Nash equilibrium is a strategy profile and should not be given in terms of • payoffs. 所謂 Nash equil. 係指策略組合, 非報酬組合

  25. Strict and nonstrict equilibria

  26. Dominant Strategy • For player 1: • T is dominated by M • T is dominated by M • M is dominated by B

  27. Cournot Game • Cournot’s duopoly game • Two firms produce identical products and competes in a market • Market demand: P(Q) = P(q1+ q2), P' (Q) < 0 • Each firm’s profit: Revenue - Costi (qi, q-i)= P(qi+ q-i) qi - Ci(qi) • Optimization: maximizing profitsFOC: i(qi, q-i)/qi = P'(qi+ q-i) qi +P - C'i 0, for i=1, 2 • Best response function (reaction curve)qi = qi(q-i) • Solve q1, q2 simultaneously to yield Nash solution

  28. Cournot Game: an example • Market DemandP=P(Q) =  - Q, Q= q1+ q2 • Common Constant Marginal CostCi = c qi , for i = 1,2 • Profitsi (qi, q-i)= ( - qi- q-i)qi - cqi • FOC:Response functioni (qi, q-i)/qi = -qi+( -qi- q-i -c)  0

  29. Profit Function in Cournot Game • Profit function:1=q1( -q1- q2 -c)given any q2when q2 = 01= q1( -q1-c) q1 = 0, -cwhen q2 > 0Profit curve shifts downward1= q1( -q1 - q2 -c)

  30. Best Response f() and Nash • Firm i’s optimal choice of qi given other’s q-i • For firm 1, FOC becomes(-1)q1+( -q1- q2 -c)  0q1 = (1/2) ( -q2 -c) • For firm 2, FOC becomes -q2+( -q1- q2 -c)  0q2 = (1/2) ( -q1 -c) • Cournot-Nash equilibriumqi* = (1/3) ( -c), for i =1, 2

  31. Reaction Curves and Nash

  32. Nash Equil. In Cournot Game

  33. A Collusive Duopoly Outcome • Two firms collude as a monopoly • They maximize joint profits and share the output • Market Demand:P=P(Q) =  - Q, • Joint Profits max  = P(Q)Q - cQ = ( - Q)Q - cQ • FOC ( - Q) -Q - c =0 => Qm* =q1+q2=(-c) /2 Each firm’s collusive output qim* = (-c) /4 < qi* = (-c) /3 • OPEC collusion

  34. A Collusive Duopoly Outcome is not a Nash equilibrium?

  35. Bertrand’s Competition • Price (cost) competition • Firms set prices to maximize profits • Consumers purchase with the lowest price • A Firm takes ALL with the lowest price. Firms share the market equally if prices are the same • The Game • Player: the firms (with cost function Ci(qi) • Strategies: each firm’s possible (non-negative) prices • Payoffs for firm i: (market demand D=  - p)piD(pi) / m - Ci(D(pi)/m)if there are m firms with the same lowest price,where m = 1 if firm i’s profits is lower than the others

  36. Profit function in Bertrand Game • Bertrand’s duopoly game • Two firms compete in the market

  37. Profits in Duopoly Bertrand • when pj < c, firm i’s profit <0 if pipj profit =0 if pi>pj • Best responseBi(pj)={pi: pi>pj} • when pj = c, similar to the aboveprofit =0 if pipj

  38. Profits in Duopoly Bertrand (2) • when c < pj pm, firm i’s profit ↑in pi if pi<pj profit = 1/2 share if pi=pj profit =0 if pi>pj • Best response seems to beempty set

  39. Profits in Duopoly Bertrand (3) • when pj > pm, firm i’s best responseBi(pj)={pi: pi=pm}

  40. Best Response f() in Bertrand

  41. Best Response Plot in Bertrand • Nash equilibrium: (p1*, p2*) = (c, c)

  42. Reasoning in Bertrand • No one should set pi < c since profit<0so, feasible strategy set is {pi c}, for i=1,2 • If firm i choose pi < pj , firm j can further lower pj to take All market. • But firm i also does the same thing. So the price continued to be lower (price war) until pi = c. • Zero-profit Nash outcome • zero profit => normal profit

More Related