Folk theorem (game theory)

For other uses, see Folk theorem.

Folk theorem
A solution concept in game theory
Relationships
Subset of	Minimax, Nash Equilibrium
Significance
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).^[1] Folk theorems are motivated by a puzzling fact: in many cases, game theory predicts that rational people will act selfishly, since selfishness is the only Nash equilibrium in the game. However, in reality, people act cooperatively. The explanation provided by folk theorems is that, in repeated games, there are many Nash equilibria which are substantially different than in the one-shot game. The fact that the game is repeated allows the players to agree on certain sequences of actions, and punish the players that deviate from that sequence.

For example, in the one-shot Prisoner's Dilemma, both players cooperating is not a Nash equilibrium (if at least one of them is rational). The only Nash equilibrium (if both are rational) is given by both players defecting, 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.

Preliminaries

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. I.e, 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 (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.^[2]

Infinitely-repeated games without discounting

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 $x_t$ , player i's utility is:

U_i = \lim_{T\to \infty} \inf \frac{1}{T} \sum_{t=0}^{T} u_i(x_t),

where $u_i$ 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^[3] or grim trigger^[4] 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.

Subgame perfection

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.^[3]|^[5]^: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.

Coalition subgame-perfect equilibria: ^[6] An equilibrium is called a coalition Nash equilibrium if no coalition can gain from deviating. It is called a coalition subgame-perfect equilibria if no coalition can gain from deviating after any history. ^[7] With the limit-of-means criterion, an outcome is attainable in coalition-Nash-equilibrium or in coalition-subgame-perfect-equilibrium, if-and-only-if it is Pareto efficient and weakly-coalition-individually-rational.^[8]

Overtaking

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 $i$ (strictly) prefers the sequence of outcomes $y_t$ over the sequence $x_t$ , if:^[4]^[6]^[5]^:139

\lim_{T\to \infty} \inf \sum_{t=0}^{T}( u_i(y_t) - u_i(x_t)) > 0

For example, consider the sequences $x=(0,0,0,0,...)$ and $y=(-1,2,0,0,...)$ . According to the limit-of-means criterion, they are equivalent but according to the overtaking criterion, $y$ is better than $x$ . 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:

Strict stationary equilibria:^[4] A Nash equilibrium is called strict if each player strictly prefers the infinite sequence of outcomes attained in equilibrium, over any othe sequence he can deviate to. A Nash equilibrium is called stationary if the outcome is the same in each time-period. An outcome is attainable in strict-stationary-equilibrium if-and-only-if for every player the outcome is strictly better than the player's minimax outcome.^[9]
Strict stationary subgame-perfect equilibria:^[4] An outcome is attainable in strict-stationary-subgame-perfect-equilibrium, if for every player the outcome is strictly better than the player's minimax outcome (note that this is not an "if-and-only-if" result). To achieve subgame-perfect equilibrium with the overtaking criterion, it is required to punish not only the player that deviates from the agreement path, but also every player that does not cooperate in punishing the deviant.^[5]^:149–150
- The "stationary equilibrium" concept can be generalized to a "periodic equilibrium", in which a finite number of outcomes is repeated periodically, and the payoff in a period is the arithmetic mean of the payoffs in the outcomes. That mean payoff should be strictly above the minimax payoff.^[4]
Strict stationary coalition equilibria: ^[6] With the overtaking criterion, if an outcome is attainable in coalition-Nash-equilibrium, then it is Pareto efficient and weakly-coalition-individually-rational. On the other hand, if it is Pareto efficient and strongly-coalition-individually-rational, strongly-coalition-individually-rational^[10] it can be attained in strict-stationary-coalition-equilibrium.

Infinitely-repeated games with discounting

Assume that the payoff of a player in an infinitely repeated game is given by the average discounted criterion with discount factor 0<δ<1:

U_i = (1-\delta) \sum_{t \geq 0} \delta^t u_i(x_t),

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).

Let a be a pure strategy profile with payoff profile x which strictly dominates the minmax payoff profile. One can define a Nash equilibrium with x as resulting payoff profile as follows:

1. All players start by playing a and continue to play a if no deviation occurs.

2. If any one player, say player i, deviated, play the strategy profile m which minmaxes i forever after.

3. Ignore multilateral deviations.

If player i gets ε more than his minmax payoff each stage by following 1, then the potential loss from punishment is

\frac{1}{1-\delta} \epsilon.

If δ is close to 1, this outweighs any finite one-stage gain, making the strategy a Nash equilibrium.

An alternative statement of this folk theorem^[2] 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 equilibirum to any desired precision (for every ε there exists a Nash equilibrium where the payoff profile is a distance ε away from x).

Subgame perfection

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.

1. All players start by playing a and continue to play a if no deviation occurs.

2. If any one player, say player i, deviated, play the strategy profile m which minmaxes i for N periods. (Choose N and δ large enough so that no player has incentive to deviate from phase 1.)

3. If no players deviated from phase 2, all player j ≠ i gets rewarded ε above j's min-max forever after, while player i continues receiving his min-max. (Full-dimensionality and the interior assumption is needed here.)

4. If player j deviated from phase 2, all players restart phase 2 with j as target.

5. Ignore multilateral deviations.

Player j ≠ i now has no incentive to deviate from the punishment phase 2. This proves the subgame perfect folk theorem.

Finitely-repeated games without discount

Assume that the payoff of a player in an finitely repeated game is given by a simple arithmetic mean:

U_i = \frac{1}{T} \sum_{t=0}^{T} u_i(h_t)

A folk theorem for this case has the following additional requirement:^[2]

In the basic game, for every player i, there is a Nash-equilibrium

E_i

that is strictly better, for i, then his minmax payoff.

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 first phase, the players alternate strategies in the required frequencies to approximate the desired payoff profile.
In the last phase, the players play the preferred equilibrium of each of the players in turn.

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.

Applications

Folk theorems can be applied to a diverse number of fields. For example:

Anthropology: in a community where all behavior is well known, and where members of the community know that they will continue to have to deal with each other, then any pattern of behavior (traditions, taboos, etc.) may be sustained by social norms so long as the individuals of the community are better off remaining in the community than they would be leaving the community (the minimax condition).
International politics: agreements between countries cannot be effectively enforced. They are kept, however, because relations between countries are long-term and countries can use "minimax strategies" against each other. This possibility often depends on the discount factor of the relevant countries. If a country is very impatient (pays little attention to future outcomes), then it may be difficult to punish it (or punish it in a credible way). As specific historic example, consider the relations between North Vietnam and the USA during the Vietnam war.^[3]

On the other hand, MIT economist Franklin Fisher has noted that the folk theorem is not a positive theory.^[11] 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.^[11]

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.^[12] 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.

Summary of folk theorems

The following table compares various folk theorems in several aspects:

Horizon – whether game is repeated Finitely or Infinitely many times.
Utilities – whether the utility of a player in the repeated game is assumed to be an arithmetic mean or a discounted sum.
Conditions on G (the basic game) – whether there are any technical conditions that should hold in the one-shot game in order for the theorem to work.
Conditions on x (the target payoff vector) – whether the theorem works for any IR and feasible payoff vector, or only on a subset of these vectors.
Equilibrium type – if all conditions are met, what kind of equilibrium is guaranteed by the theorem – Nash or Subgame-perfect?
Punishment type – what kind of punishment strategy is used to deter players from deviating?

Published by	Horizon	Utilities	Conditions on G	Conditions on x	Guarantee	Equilibrium type	Punishment type
Benoit& Krishna^[13]	Finite ( $T$ )	Arithmetic mean	For every player there is an equilibrium payoff strictly better than minimax.	None	For all $\epsilon>0$ there is $T_0\in N$ such that, if $T\geq T_0$ , for every $x$ there is equilibrium with payoff $\epsilon$ -close to $x$ .	Nash
Aumann& Shapley^[3]	Infinite	Limit of means	None	None	Payoff exactly $x$ .	Nash	Grim
Aumann& Shapley^[3] and Rubinstein^[6]^[14]	Infinite	Limit of means	None	None	Payoff exactly $x$ .	Subgame-perfect	Limited-time punishment.^[5]^:146–149
Rubinstein^[4]	Infinite	Overtaking	None	Strictly above minimax.	Single outcome or a periodic sequence.	Subgame-perfect	Punishing non-punishers.^[5]^:149–150
Rubinstein^[6]	Infinite	Limit of means	None	Pareto-efficient and weakly-coalition-individually-rational^[8]	None	Coalition-subgame-perfect
Rubinstein^[6]	Infinite	Overtaking	None	Pareto-efficient and strongly-coalition-individually-rational^[10]	None	Coalition-Nash
Fudenberg& Maskin^[15]	Infinite	Sum with discount $\delta$	Correlated mixed strategies are allowed.	Strictly above minimax.	When $\delta$ is sufficiently near 1, there is an equilibrium with payoff exactly $x$ .	Nash	Grim
Fudenberg& Maskin^[15]	Infinite	Sum with discount $\delta$	Only pure strategies are allowed.	Strictly above minimax.	For all $\epsilon>0$ there is $\delta_0<1$ such that, if $\delta\geq \delta_0$ , for every $x$ there is an equilibrium with payoff $\epsilon$ -close to $x$ .	Nash	Grim punishment.
Friedman (1971,1977)	Infinite	Sum with discount $\delta$	Correlated mixed strategies are allowed.	Strictly above a Nash-equilibrium in G.	When $\delta$ is sufficiently near 1, there is equilibrium with payoff exactly $x$ .	Subgame-perfect	Grim punishment using the Nash-equilibrium.
Fudenberg& Maskin^[15]	Infinite	Sum with discount $\delta$	Two players	Strictly above minimax.	For all $x$ there is $\delta_0<1$ such that, if $\delta\geq \delta_0$ , there is equilibrium with payoff exactly $x$ .	Subgame-perfect	Limited-time punishment.
Fudenberg& Maskin^[15]	Infinite	Sum with discount $\delta$	The IR feasible space is full-dimensional.^[16]	Strictly above minimax.	For all $x$ there is $\delta_0<1$ such that, if $\delta\geq \delta_0$ , there is equilibrium with payoff exactly $x$ .	Subgame-perfect	Rewarding the punisheres.^[5]^:150–153

Notes

↑ In mathematics, the term folk theorem refers generally to any theorem that is believed and discussed, but has not been published. In order that the name of the theorem be more descriptive, Roger Myerson has recommended the phrase general feasibility theorem in the place of folk theorem for describing theorems which are of this class. See Myerson, Roger B. Game Theory, Analysis of conflict, Cambridge, Harvard University Press (1991)
1 2 3 Michael Maschler, Eilon Solan & Shmuel Zamir (2013). Game Theory. Cambridge University Press. pp. 176–180. ISBN 978-1-107-00548-8.
1 2 3 4 5 Aumann, Robert J.; Shapley, Lloyd S. (1994). "Long-Term Competition—A Game-Theoretic Analysis". Essays in Game Theory. p. 1. doi:10.1007/978-1-4612-2648-2_1. ISBN 978-1-4612-7621-0.
1 2 3 4 5 6 Rubinstein, Ariel (1979). "Equilibrium in supergames with the overtaking criterion". Journal of Economic Theory 21: 1. doi:10.1016/0022-0531(79)90002-4.
1 2 3 4 5 6 . ISBN 0-262-15041-7. LCCN 94008308. OL 1084491M. Missing or empty |title= (help)
1 2 3 4 5 6 Rubinstein, A. (1980). "Strong perfect equilibrium in supergames". International Journal of Game Theory 9: 1. doi:10.1007/BF01784792.
↑ The paper uses the term "strong equilibrium". Here, to prevent ambiguity, the term "coalition equilibrium" is used instead.
1 2 For every nonempty coalition $B$ , there is a strategy of the other players ( $N\setminus B$ ) such that for any strategy played by $B$ , the payoff when $B$ plays $c^B$ is not [strictly better for all members of $B$ ].
↑ In the 1979 paper, Rubinstein claims that an outcome is attainable in strict-stationary-equilibrium if-and-only-if for every player, the outcome is EITHER strictly better than the player's minimax outcome OR the outcome is weakly better than any other outcome the player can unilaterally deviate to. It is not clear how the second option is attainable in a strict equilibrium. In the 1994 book, this claim does not appear.
1 2 For every nonempty coalition $B$ , there is a strategy of the other players ( $N\setminus B$ ) such that for any strategy played by $B$ , the payoff is strictly worse for at least one member of $B$ .
1 2 Fisher, Franklin M. Games Economists Play: A Noncooperative View The RAND Journal of Economics, Vol. 20, No. 1. (Spring, 1989), pp. 113–124, this particular discussion is on page 118
↑ Christian Borgs, Jennifer Chayes, Nicole Immorlica, Adam Tauman Kalai, Vahab Mirrokni, and Christos Papadimitriou (2007). "The Myth of the Folk Theorem" (PDF).
↑ Benoit, Jean-Pierre; Krishna, Vijay (1985). "Finitely Repeated Games". Econometrica 53 (4): 905. doi:10.2307/1912660. JSTOR 1912660.
↑ Rubinstein, Ariel (1994). "Equilibrium in Supergames". Essays in Game Theory. p. 17. doi:10.1007/978-1-4612-2648-2_2. ISBN 978-1-4612-7621-0.
1 2 3 4 Fudenberg, Drew; Maskin, Eric (1986). "The Folk Theorem in Repeated Games with Discounting or with Incomplete Information". Econometrica 54 (3): 533. doi:10.2307/1911307. JSTOR 1911307.
↑ There is a collection of IR feasible outcomes $y_1,\dots,y_n$ , one per player, such that for every players $i,j$ , $x_i > y_{i,i}$ and $y_{j,i} > y_{i,i}$ .

References

Friedman, J. (1971), "A non-cooperative equilibrium for supergames", Review of Economic Studies 38 (1): 1–12, doi:10.2307/2296617, JSTOR 2296617 .
Mas-Colell, A., Whinston, M and Green, J. (1995) Microeconomic Theory, Oxford University Press, New York (readable; suitable for advanced undergraduates.)
Tirole, J. (1988) The Theory of Industrial Organization, MIT Press, Cambridge MA (An organized introduction to industrial organization)
Ratliff, J. (1996). A Folk Theorem Sampler. A set of introductory notes to the Folk Theorem.

Topics in game theory

Definitions	Normal-form game Extensive-form game Escalation of commitment Graphical game Cooperative game Succinct game Information set Hierarchy of beliefs Preference

Equilibrium concepts	Nash equilibrium Subgame perfection Mertens-stable equilibrium Bayesian-Nash Perfect Bayesian Trembling hand Proper equilibrium Epsilon-equilibrium Correlated equilibrium Sequential equilibrium Quasi-perfect equilibrium Evolutionarily stable strategy Risk dominance Core Shapley value Pareto efficiency Quantal response equilibrium Self-confirming equilibrium Strong Nash equilibrium Markov perfect equilibrium

Strategies	Dominant strategies Pure strategy Mixed strategy Tit for tat Grim trigger Collusion Backward induction Forward induction Markov strategy

Classes of games	Symmetric game Perfect information Simultaneous game Sequential game Repeated game Signaling game Cheap talk Zero-sum game Mechanism design Bargaining problem Stochastic game n-player game Large Poisson game Nontransitive game Global games Strictly determined game

Games	Prisoner's dilemma Traveler's dilemma Coordination game Chicken Centipede game Volunteer's dilemma Dollar auction Battle of the sexes Stag hunt Matching pennies Ultimatum game Rock-paper-scissors Pirate game Dictator game Public goods game Blotto games War of attrition El Farol Bar problem Fair division Fair cake-cutting Cournot game Deadlock Diner's dilemma Guess 2/3 of the average Kuhn poker Nash bargaining game Screening game Prisoners and hats puzzle Trust game Princess and monster game Monty Hall problem Rendezvous problem

Theorems	Minimax theorem Nash's theorem Purification theorem Folk theorem Revelation principle Arrow's impossibility theorem

Key figures	Albert W. Tucker Amos Tversky Ariel Rubinstein Daniel Kahneman David K. Levine David M. Kreps Donald B. Gillies Drew Fudenberg Eric Maskin Harold W. Kuhn Herbert Simon Hervé Moulin Jean Tirole Jean-François Mertens John Harsanyi John Maynard Smith John Nash John von Neumann Kenneth Arrow Kenneth Binmore Leonid Hurwicz Lloyd Shapley Melvin Dresher Merrill M. Flood Oskar Morgenstern Paul Milgrom Peyton Young Reinhard Selten Robert Aumann Robert B. Wilson Roger Myerson Samuel Bowles Thomas Schelling William Vickrey

See also	All-pay auction Alpha–beta pruning Bertrand paradox Bounded rationality Combinatorial game theory Confrontation analysis Coopetition List of game theorists List of games in game theory No-win situation Tragedy of the commons Tyranny of small decisions

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