Repeated Games - UCSB Department of Economics

Repeated Games - UCSB Department of Economics
Repeated Games
• This week we examine the effect of repetition on strategic
behavior in games with perfect information.
• If a game is played repeatedly, with the same players, the
players may behave very differently than if the game is
played just once (a one-shot game), e.g., repeatedly borrow a
friend’s car versus renting a car.
• Two types of repeated games:
– Finitely repeated: the game is played for a finite and
known number of rounds, for example, 2
rounds/repetitions.
– Infinitely or Indefinitely repeated: the game has no
predetermined length; players act as though it will be
played indefinitely, or it ends only with some probability.
Finitely Repeated Games
• Writing down the strategy space for repeated games is
difficult, even if the game is repeated just 2 rounds. For
example, consider the finitely repeated game strategies for
L
R
the following 2x2 game played just twice.
U
• For a row player:
D
– U1 or D1 Two possible moves in round 1 (subscript 1).
– For each first round history pick whether to go U2 or D2
The histories are:
(U1,L1) (U1,R1) (D1,L1) (D1,R1)
2 + 2 + 2 + 2
– 8 possible strategies, 16 strategy profiles!
Strategic Form of a 2-Round Finitely
Repeated Game
• This quickly gets messy!
L2
L2
R2
U2
U2
L1
D2
L2
U2
D2
R2
R2
R1
D2
U1
D1
L2
U2
D2
R2
Finite Repetition of a Game with a
Unique Equilibrium
• Fortunately, we may be able to determine how to play a finitely repeated
game by looking at the equilibrium or equilibria in the one-shot or “stage
game” version of the game.
• For example, consider a 2x2 game with a unique equilibrium, e.g. the
Prisoner’s Dilemma: higher numbers=years in prison, are worse.
• Does the equilibrium change if this game is played just 2 rounds?
A Game with a Unique Equilibrium Played
Finitely Many Times Always Has the Same
Subgame Perfect Equilibrium Outcome
• To see this, apply backward induction to the finitely repeated
game to obtain the subgame perfect Nash equilibrium (spne).
• In the last round, round 2, both players know that the game
will not continue further. They will therefore both play their
dominant strategy of Confess.
• Knowing the results of round 2 are Confess, Confess, there is
no benefit to playing Don’t Confess in round 1. Hence, both
players play Confess in round 1 as well.
• As long as there is a known, finite end, there will be no change
in the equilibrium outcome of a game with a unique
equilibrium. This is also true for zero or constant sum games.
Finite Repetition of a Sequential Move Game
• Recall the incumbent-rival game:
• In the one-shot, sequential move game there is a unique
subgame perfect equilibrium where the rival enters and the
incumbent accommodates.
• Does finite repetition of this game change the equilibrium?
• Should it?
The Chain Store Paradox
• Selten (1978) proposed a finitely repeated version of the incumbent-rival
(entry) game in which the incumbent firm is a monopolist with a chain of
stores in 20 different locations.
• He imagined that in each location the chain store monopolist was
challenged by a local rival firm, indexed by f=1,2,…20.
• The game is played sequentially: firm 1 decides whether to enter or not at
location 1, chain store decides to fight, accommodate, then firm 2, etc.
• Consider the last rival, firm 20. Since the incumbent gains nothing by
fighting this last firm and does better by accommodating, he will
accommodate, and firm 20 will therefore choose to enter. But if the
incumbent will accommodate firm 20, there is nothing he gains from
fighting firm 19, etc.
• By backward induction, each firm f=1,2…20 chooses Enter and the
Incumbent always chooses Accommodate. This game theoretic solution is
what Selten calls the “induction hypothesis”.
What about Deterrence?
•
•
•
•
•
•
Selten noted that while the induction argument is the logically correct, gametheoretic solution assuming rationality and common knowledge of the structure
of the game, it does not seem empirically plausible – why?
Under the enter/accommodate equilibrium, the incumbent earns a payoff of
2x20 =40. But perhaps he can do better, for instance, suppose the incumbent
chooses to fight the first 15 rivals and accommodate the last 5.
If this strategy this is common knowledge then the first 15 stay out and earn a
payoff of 1 each, while the incumbent earns 5x15+2x5=85>40.
Even if some of the first 15 rivals choose to enter anyway, say (2/5ths=6), the
incumbent can still be better off; in that case he gets 5x(15-6)+2x5=55>40!
This contradiction between the game theoretic solution and an empirically
plausible “deterrence hypothesis” is what Selten labeled the chain-store paradox.
The paradox results from the game theoretic assumption that all players presume
one another to be perfectly rational and know (via common knowledge) the
structure of the game. They are thus led to conclude that the incumbent will
never, ever fight. By this standard, fighting would be an irrational move and
would never be observed.
Finite Repetition of a Simultaneous Move Game with
Multiple Equilibria: The Game of Chicken
• Consider 2 firms playing the following one-stage Chicken game.
• The two firms play the game N>1 times, where N is known. What are
the possible subgame perfect equilibria?
• In the one-shot “stage game” there are 3 equilibria, Ab, Ba and a
mixed strategy where row plays A and column plays a with probability
½, and the expected payoff to each firm is 2.
Games with Multiple Equilibria Played Finitely
Many Times Have Many Subgame Perfect Equilibria
Some subgame perfect equilibrium of the finitely repeated
version of the stage game are:
1. Ba, Ba, ....
N times
2. Ab, Ab, ...
N times
3. Ab, Ba, Ab, Ba,...
N times
4. Aa, Ab, Ba
N=3 rounds.
Strategies Supporting these Subgame
Perfect Equilibria
1. Ba, Ba,... Row Firm first move: Play B
Avg. Payoffs:
(4, 1)
Second move: After every possible history play B.
Column Firm first move: Play a
Second move: After every possible history play a.
2. Ab, Ab,... Row Firm first move: Play A
Avg. Payoffs:
(1, 4)
Second move: After every possible history play A.
Column Firm first move: Play b
Second move: After every possible history play b.
3. Ab, Ba, Ab, Ba,.. Row Firm first round move: Play A
Avg. Payoffs:
(5/2, 5/2)
Even rounds: After every possible history play B.
Odd rounds: After every possible history play A.
Column Firm first round move: Play b
Even rounds: After every possible history play a
Odd rounds: After every possible history play b.
What About that 3-Round S.P. Equilibrium?
4. Aa, Ab, Ba (3 Rounds only) can be supported by the strategies:
Row Firm first move: Play A
Second move:
– If history is (A,a) or (B,b) play A, and play B in round 3 unconditionally.
– If history is (A,b) play B, and play B in round 3 unconditionally.
– If history is (B,a) play A, and play A in round 3 unconditionally.
Column Firm first move: Play a
Second move:
– If history is (A,a) or (B,b) play b, and play a in round 3 unconditionally.
– If history is (A,b) play a, and play a in round 3 unconditionally.
– If history is (B,a) play b, and play b in round 3 unconditionally.
Avg. Payoff to Row = (3+1+4)/3 = Avg. Payoff to Column: (3+4+1)/3 = 2.67.
More generally if N=101 then, Aa, Aa, Aa,...99 followed by Ab, Ba is also a s.p. eq.
Why is this a Subgame Perfect Equilibrium?
• Because Aa, Ab, Ba is each player’s best response to the
other player’s strategy at each subgame.
• Consider the column player. Suppose he plays b in round 1,
and row sticks to the plan of A. The round 1 history is (A,b).
– According to Row’s strategy given a history of (A,b),
Row will play B in round 2 and B in round 3.
– According to Column’s strategy given a history of (A,b),
Column will play a in round 2 and a in round 3.
• Column player’s average payoff is (4+1+1)/3 = 2. This is
less than the payoff it earns in the subgame perfect
equilibrium which was found to be 2.67. Hence, column
player will not play b in the first round given his strategy
and the Row player’s strategies.
• Similar argument for the row firm.
Summary
• A repeated game is a special kind of game (in extensive or
strategic form) where the same one-shot “stage” game is
played over and over again.
• A finitely repeated game is one in which the game is played a
fixed and known number of times.
• If a simultaneous move game has a unique Nash equilibrium,
or a sequential move game has a unique subame perfect Nash
equilibrium this equilibrium is also the unique subgame
perfect equilibrium of the finitely repeated game.
• If a simultaneous move game has multiple Nash equilibria,
then there are many subgame perfect equilibria of the finitely
repeated game. Some of these involve the play of strategies
that are collectively more profitable for players than the oneshot stage game Nash equilibria, (e.g. Aa, Ba, Ab in the last
game studied).
Infinitely Repeated Games
• Finitely repeated games are interesting, but relatively rare;
how often do we really know for certain when a game we
are playing will end? (Sometimes, but not often).
• Some of the predictions for finitely repeated games do not
hold up well in experimental tests:
– The unique subgame perfect equilibrium in the finitely repeated
ultimatum game or prisoner’s dilemma game (always confess) are
not usually observed in all rounds of finitely repeated games.
• On the other hand, we routinely play many games that are
indefinitely repeated (no known end). We call such games
infinitely repeated games, and we now consider how to
find subgame perfect equilibria in these games.
Discounting in Infinitely Repeated Games
• Recall from our earlier analysis of bargaining, that players
may discount payoffs received in the future using a constant
discount factor, = 1/(1+r), where 0 <  < 1.
– For example, if =.80, then a player values $1 received one period in
the future as being equivalent to $0.80 right now (x$1). Why? Because
the implicit one period interest rate r=.25, so $0.80 received right now
and invested at the one-period rate r=.25 gives (1+.25) x$0.80 = $1 in
the next period.
• Now consider an infinitely repeated game. Suppose that an
outcome of this game is that a player receives $p in every
future play (round) of the game.
• The value of this stream of payoffs right now is :
$p ( + 2 + 3 + ..... )
• The exponential terms are due to compounding of interest.
Discounting in Infinitely Repeated Games, Cont.
• The infinite sum,    2   3  ... converges to

1 
• Simple proof: Let x=    2   3  ...
Notice that x =    (   2   3  ...)    x

solve x    x for x : (1   ) x   ; x 
1 
• Hence, the present discounted value of receiving $p in every
future round is $p[/(1-)] or $p/(1-)
• Note further that using the definition, =1/(1+r), /(1-) =
[1/(1+r)]/[1-1/(1+r)]=1/r, so the present value of the infinite
sum can also be written as $p/r.
• That is, $p/(1-) = $p/r, since by definition, =1/(1+r).
The Prisoner’s Dilemma Game (Again!)
• Consider a new version of the prisoner’s dilemma game,
where higher payoffs are now preferred to lower payoffs.
C
C
D
D
c,c
a,b
b,a
d,d
C=cooperate,
(don’t confess)
D=defect (confess)
• To make this a prisoner’s dilemma, we must have:
b>c >d>a. We will use this example in what follows.
C
C
D
D
4, 4
0, 6
6, 0
2, 2
Suppose the payoffs
numbers
are in dollars
Sustaining Cooperation in the Infinitely
Repeated Prisoner’s Dilemma Game
• The outcome C,C forever, yielding payoffs (4,4) can be a
subgame perfect equilibrium of the infinitely repeated prisoner’s
dilemma game, provided that 1) the discount factor that both
players use is sufficiently large and 2) each player uses some kind
of contingent or trigger strategy. For example, the grim trigger
strategy:
– First round: Play C.
– Second and later rounds: so long as the history of play has been (C,C) in
every round, play C. Otherwise play D unconditionally and forever.
• Proof: Consider a player who follows a different strategy, playing
C for awhile and then playing D against a player who adheres to
the grim trigger strategy.
Cooperation in the Infinitely Repeated
Prisoner’s Dilemma Game, Continued
• Consider the infinitely repeated game starting from the round in
which the “deviant” player first decides to defect. In this round
the deviant earns $6, or $2 more than from C, $6-$4=$2.
• Since the deviant player chose D, the other player’s grim trigger
strategy requires the other player to play D forever after, and so
both will play D forever, a loss of $4-$2=$2 in all future rounds.
• The present discounted value of a loss of $2 in all future rounds
is $2/(1-)
• So the player thinking about deviating must consider whether
the immediate gain of 2 > 2/(1-), the present value of all future
lost payoffs, or if 2(1-) > 2, or 2 >4, or 1/2 > .
• If ½ <  < 1, the inequality does not hold, and so the player
thinking about deviating is better off playing C forever.
Other Subgame Perfect Equilibria are Possible
in the Repeated Prisoner’s Dilemma Game
• The “Folk theorem” of repeated games says that almost any outcome
that on average yields the mutual defection payoff or better to both
players can be sustained as a subgame perfect Nash equilibrium of the
indefinitely repeated Prisoner’s Dilemma game.
Row Player
Avg. Payoff
The set of subgame perfect
Nash Equilibria, is the green
area, as determined by average
payoffs from all rounds played
(for large enough discount factor, ).
Mutual
defection-in-all
rounds equilibrium
The efficient, mutual cooperation-in
all-rounds equilibrium outcome is
here, at 4,4.
The set of feasible
payoffs is the union of the
green and yellow regions
Column Player
Avg. Payoff
Must We Use a Grim Trigger Strategy to Support
Cooperation as a Subgame Perfect Equilibrium in the
Infinitely Repeated PD?
• There are “nicer” strategies that will also support (C,C) as an
equilibrium.
• Consider the “tit-for-tat” (TFT) strategy (row player version)
– First round: Play C.
– Second and later rounds: If the history from the last round is (C,C) or
(D,C) play C. If the history from the last round is (C,D) or (D,D) play D.
• This strategy “says” play C initially and as long as the other
player played C last round. If the other player played D last
round, then play D this round. If the other player returns to
playing C, play C at the next opportunity, else play D.
• TFT is forgiving, while grim trigger (GT) is not. Hence TFT is
regarded as being “nicer.”
TFT Supports (C,C) forever as a NE in the Infinitely
Repeated PD
• Proof. Suppose both players play TFT. Since the strategy
specifies that both players start off playing C, and continue to
play C so long as the history includes no defections, the history
of play will be
(C,C), (C,C), (C,C), ......
• Now suppose the Row player considers deviating in one round
only and then reverting to playing C in all further rounds, while
Player 2 is assumed to play TFT.
• Player 1’s payoffs starting from the round in which he deviates
are: 6, 0, 4, 4, 4,..... If he never deviated, he would have gotten
the sequence of payoffs 4, 4, 4, 4, 4,... So the relevant
comparison is whether 6+0 > 4+4. The inequality holds if
2>4 or ½ > . So if ½ < < 1, the deviation is not profitable.
• No other profitable deviations if ½ <  < 1.
TFT as an Equilibrium Strategy
is not Subgame Perfect
• To be subgame perfect, an equilibrium strategy must prescribe
best responses after every possible history, even those with
zero probability under the given strategy.
• Consider two TFT players, and suppose that the row player
“accidentally” deviates to playing D for one round – “a zero
probability event” - but then continues playing TFT as before.
• Starting with the round of the deviation, the history of play
will look like this: (D,C), (C,D), (D,C), (C,D),..... Why? Just
apply the TFT strategy.
• Consider the payoffs to the column player 2 starting from
round 2
6  0  6 2  0 3  6 4  0 5  ...
 6  6( 2   4  ...)
 6  6 2 /(1   2 )  6 /(1   2 ).
TFT is not Subgame Perfect, cont’d.
• If the column player 2 instead played C in round 2 and then continued
with TFT (a one-shot deviation), the history would become:
(D,C), (C,C), (C,C), (C,C).....
• In this case, the payoffs to the column player 2 starting from round 2
would be:
2
3
4  4  4  4 ...
 4  4(   2   3  ...),
 4  4 /(1   )  4 /(1   )
• Column player 2 asks whether
6 /(1   2 )  4(1   )
 4 2  6  2  0, which is false for any 1 / 2    1.
• Column player 2 reasons that it is better to deviate from TFT!
One-Shot Deviation Principle
• Above example is illustration of the one-shot deviation principle
• The strategy profile of an infinitely repeated game is SPE if and only if
there is no profitable one-shot deviation starting from any history.
Must We Discount Payoffs?
• Answer 1: How else can we distinguish between infinite
sums of different constant payoff amounts?
• Answer 2: We don’t have to assume that players discount
future payoffs. Instead, we can assume that there is some
constant, known probability q, 0 < q < 1, that the game will
continue from one round to the next. Assuming this
probability is independent from one round to the next, the
probability the game is still being played T rounds from
right now is qT.
– Hence, a payoff of $p in every future round of an infinitely repeated
game with a constant probability q of continuing from one round to
the next has a value right now that is equal to:
$p(q+q2+q3+....) = $p[q/(1-q)].
– Similar to discounting of future payoffs; equivalent if q=.
Play of a Prisoner’s Dilemma with
an Indefinite End
• Let’s play the Prisoner’s Dilemma game studied today but
with a probability q=.8 that the game continues from one
round to the next.
• What this means is that at the end of each round the
computer program draws a random number between 0 and
1. If this number is less than or equal to .80, the game
continues with another round. Otherwise the game ends.
• We refer to the game with an indefinite number of
repetitions of the stage game as a supergame.
• The expected number of rounds in the supergame is:
1+q+q2+q3+ …..= 1/(1-q)=1/.2 = 5; In practice, you may
play more than 5 rounds or less than 5 rounds in the
supergame: it just depends on the sequence of random
draws.
Data from an Indefinitely Repeated
Prisoner’s Dilemma Game with Fixed Pairings
• From Duffy and Ochs, Games and Economic Behavior, 2009
Fixed Pairings, 14 Subjects
Average Cooperation Frequency of 7 pairs
% X (Cooperate)
1
0.8
0.6
0.4
0.2
0
1
4
7 10 13 1
4
7
2
2
2
5
8
3
6
9 12 15 18 21 1
4
3
3
6
9 12 15 18 21 24 27 30 3
6
9 12 15 18
Round Number (1 Corresponds to the Start of a New Game)
• Discount factor =.90 =probability of continuation
• The start of each new supergame is indicated by a vertical line at round 1.
• Cooperation rates start at 30% and increase to 80% over 10 supergames.
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