|A solution concept in game theory|
|Subset of||Minimax, Nash equilibrium|
|Proposed by||various, notably Ariel Rubinstein|
|Used for||repeated games|
|Example||Repeated prisoner's dilemma|
In game theory, folk theorems are a class of theorems about possible Nash equilibrium payoff profiles in repeated games (Friedman 1971). The original Folk Theorem concerned the payoffs of all the Nash equilibria of an infinitely repeated game. This result was called the Folk Theorem because it was widely known among game theorists in the 1950s, even though no one had published it. Friedman's (1971) Theorem concerns the payoffs of certain subgame-perfect Nash equilibria (SPE) of an infinitely repeated game, and so strengthens the original Folk Theorem by using a stronger equilibrium concept subgame-perfect Nash equilibria rather than Nash equilibrium.
The Folk Theorem suggests that if the player is patient enough and far-sighted (i.e. if discount factor ) then not only can repeated interaction allow many SPE outcomes, but actually SPE can allow virtually any outcome in the sense of average payoffs. Put more simply, the theorem suggests that anything that is feasible and individually rational is possible.
For example, in the one-shot Prisoner's Dilemma, if both players cooperate that is not a Nash equilibrium. The only Nash equilibrium is that both players defect, which is also a mutual minmax profile. One folk theorem says that, in the infinitely repeated version of the game, provided players are sufficiently patient, there is a Nash equilibrium such that both players cooperate on the equilibrium path. But in finitely repeated game by using backward induction it can be determined that players play Nash equilibrium in the last period of the game (which is to defect).
Any Nash equilibrium payoff in a repeated game must satisfy two properties:
1. Individual rationality (IR): the payoff must weakly dominate the minmax payoff profile of the constituent stage game. That is, the equilibrium payoff of each player must be at least as large as the minmax payoff of that player. This is because a player achieving less than his minmax payoff always has incentive to deviate by simply playing his minmax strategy at every history.
2. Feasibility: the payoff must be a convex combination of possible payoff profiles of the stage game. This is because the payoff in a repeated game is just a weighted average of payoffs in the basic games.
Folk theorems are partially converse claims: they say that, under certain conditions (which are different in each folk theorem), every payoff that is both IR and feasible can be realized as a Nash equilibrium payoff profile in the repeated game.
There are various folk theorems; some relate to finitely-repeated games while others relate to infinitely-repeated games.
In the undiscounted model, the players are patient. They don't differentiate between utilities in different time periods. Hence, their utility in the repeated game is represented by the sum of utilities in the basic games.
When the game is infinite, a common model for the utility in the infinitely-repeated game is the infimum of the limit of means. If game results in a path of outcomes , player i's utility is:
where is the basic-game utility function of player i'.
An infinitely-repeated game without discounting is often called a "supergame".
The folk theorem in this case is very simple and contains no pre-conditions: every IR feasible payoff profile in the basic game is an equilibrium payoff profile in the repeated game.
The proof employs what is called grim or grim trigger strategy. All players start by playing the prescribed action and continue to do so until someone deviates. If player i deviates, all players switch to the strategy which minmaxes player i forever after. The one-stage gain from deviation contributes 0 to the total utility of the player. The utility of a deviating player cannot be higher than his minmax payoff. Hence all players stay on the intended path.
The above Nash equilibrium is not always subgame perfect. If punishment is costly for the punishers, the threat of punishment is not credible.
A subgame perfect equilibrium requires a slightly more complicated strategy.:146-149 The punishment should not last forever; it should last only a finite time which is sufficient to wipe out the gains from deviation. After that, the other players should return to the equilibrium path.
The limit-of-means criterion ensures that any finite-time punishment has no effect on the final outcome. Hence, limited-time punishment is a subgame-perfect equilibrium.
Some authors claim that the limit-of-means criterion is unrealistic, because it implies that utilities in any finite time-span contribute 0 to the total utility. However, if the utilities in any finite time-span contribute a positive value, and the value is undiscounted, then it is impossible to attribute a finite numeric utility to an infinite outcome sequence. A possible solution to this problem is that, instead of defining a numeric utility for each infinite outcome sequence, we just define the preference relation between two infinite sequences. We say that agent (strictly) prefers the sequence of outcomes over the sequence , if::139
For example, consider the sequences and . According to the limit-of-means criterion, they are equivalent but according to the overtaking criterion, is better than . See overtaking criterion for more information.
The folk theorems with the overtaking criterion are slightly weaker than with the limit-of-means criterion. Only outcomes that are strictly individually rational, can be attained in Nash equilibrium. This is because, if an agent deviates, he gains in the short run, and this gain can be wiped out only if the punishment gives the deviator strictly less utility than the agreement path. The following folk theorems are known for the overtaking criterion:
Assume that the payoff of a player in an infinitely repeated game is given by the average discounted criterion with discount factor 0 < ? < 1:
The discount factor indicates how patient the players are.
The folk theorem in this case requires that the payoff profile in the repeated game strictly dominates the minmax payoff profile (i.e., each player receives strictly more than the minmax payoff).
If player i gets ? more than his minmax payoff each stage by following 1, then the potential loss from punishment is
If ? is close to 1, this outweighs any finite one-stage gain, making the strategy a Nash equilibrium.
An alternative statement of this folk theorem allows the equilibrium payoff profile x to be any IR feasible payoff profile; it only requires there exists an IR feasible payoff profile x, which strictly dominates the minmax payoff profile. Then, the folk theorem guarantees that it is possible to approach x in equilibrium to any desired precision (for every ? there exists a Nash equilibrium where the payoff profile is a distance ? away from x).
Attaining a subgame perfect equilibrium in discounted games is more difficult than in undiscounted games. The cost of punishment does not vanish (as with the limit-of-means criterion). It is not always possible to punish the non-punishers endlessly (as with the overtaking criterion) since the discount factor makes punishments far away in the future irrelevant for the present. Hence, a different approach is needed: the punishers should be rewarded.
This requires an additional assumption, that the set of feasible payoff profiles is full dimensional and the min-max profile lies in its interior. The strategy is as follows.
Player j ? i now has no incentive to deviate from the punishment phase 2. This proves the subgame perfect folk theorem.
Assume that the payoff of a player in an finitely repeated game is given by a simple arithmetic mean:
A folk theorem for this case has the following additional requirement:
This requirement is stronger than the requirement for discounted infinite games, which is in turn stronger than the requirement for undiscounted infinite games.
This requirement is needed because of the last step. In the last step, the only stable outcome is a Nash-equilibrium in the basic game. Suppose a player i gains nothing from the Nash equilibrium (since it gives him only his minmax payoff). Then, there is no way to punish that player.
On the other hand, if for every player there is a basic equilibrium which is strictly better than minmax, a repeated-game equilibrium can be constructed in two phases:
In the last phase, no player deviates since the actions are already a basic-game equilibrium. If an agent deviates in the first phase, he can be punished by minmaxing him in the last phase. If the game is sufficiently long, the effect of the last phase is negligible, so the equilibrium payoff approaches the desired profile.
Folk theorems can be applied to a diverse number of fields. For example:
On the other hand, MIT economist Franklin Fisher has noted that the folk theorem is not a positive theory. In considering, for instance, oligopoly behavior, the folk theorem does not tell the economist what firms will do, but rather that cost and demand functions are not sufficient for a general theory of oligopoly, and the economists must include the context within which oligopolies operate in their theory.
In 2007, Borgs et al. proved that, despite the folk theorem, in the general case computing the Nash equilibria for repeated games is not easier than computing the Nash equilibria for one-shot finite games, a problem which lies in the PPAD complexity class. The practical consequence of this is that no efficient (polynomial-time) algorithm is known that computes the strategies required by folk theorems in the general case.
The following table compares various folk theorems in several aspects:
|Published by||Horizon||Utilities||Conditions on G||Conditions on x||Guarantee||Equilibrium type||Punishment type|
|Benoit& Krishna||Finite ()||Arithmetic mean||For every player there is an equilibrium payoff strictly better than minimax.||None||For all there is such that, if , for every there is equilibrium with payoff -close to .||Nash|
|Aumann& Shapley||Infinite||Limit of means||None||None||Payoff exactly .||Nash||Grim|
|Aumann& Shapley and Rubinstein||Infinite||Limit of means||None||None||Payoff exactly .||Subgame-perfect||Limited-time punishment.:146-149|
|Rubinstein||Infinite||Overtaking||None||Strictly above minimax.||Single outcome or a periodic sequence.||Subgame-perfect||Punishing non-punishers.:149-150|
|Rubinstein||Infinite||Limit of means||None||Pareto-efficient and weakly-coalition-individually-rational||None||Coalition-subgame-perfect|
|Rubinstein||Infinite||Overtaking||None||Pareto-efficient and strongly-coalition-individually-rational||None||Coalition-Nash|
|Fudenberg& Maskin||Infinite||Sum with discount||Correlated mixed strategies are allowed.||Strictly above minimax.||When is sufficiently near 1, there is an equilibrium with payoff exactly .||Nash||Grim|
|Fudenberg& Maskin||Infinite||Sum with discount||Only pure strategies are allowed.||Strictly above minimax.||For all there is such that, if , for every there is an equilibrium with payoff -close to .||Nash||Grim punishment.|
|Friedman (1971, 1977)||Infinite||Sum with discount||Correlated mixed strategies are allowed.||Strictly above a Nash-equilibrium in G.||When is sufficiently near 1, there is equilibrium with payoff exactly .||Subgame-perfect||Grim punishment using the Nash-equilibrium.|
|Fudenberg& Maskin||Infinite||Sum with discount||Two players||Strictly above minimax.||For all there is such that, if , there is equilibrium with payoff exactly .||Subgame-perfect||Limited-time punishment.|
|Fudenberg& Maskin||Infinite||Sum with discount||The IR feasible space is full-dimensional.||Strictly above minimax.||For all there is such that, if , there is equilibrium with payoff exactly .||Subgame-perfect||Rewarding the punishers.:150-153|