Two-person variable-sum games
Much of the early work in game theory was on two-person constant-sum games because they are the easiest to treat mathematically. The players in such games have diametrically opposed interests, and there is a consensus about what constitutes a solution (as given by the minimax theorem). Most games that arise in practice, however, are variable-sum games; the players have both common and opposed interests. For example, a buyer and a seller are engaged in a variable-sum game (the buyer wants a low price and the seller a high one, but both want to make a deal), as are two hostile nations (they may disagree about numerous issues, but both gain if they avoid going to war).
Some “obvious” properties of two-person constant-sum games are not valid in variable-sum games. In constant-sum games, for example, both players cannot gain (they may or may not lose, but they cannot both gain) if they are deprived of some of their strategies. In variable-sum games, however, players may gain if some of their strategies are no longer available. This might not seem possible at first. One would think that if a player benefited from not using certain strategies, the player would simply avoid those strategies and choose more advantageous ones, but this is not always the case. For example, in a region with high unemployment a worker may be willing to accept a lower salary to obtain or keep a job, but if a minimum wage law makes that option illegal, the worker may be “forced” to accept a higher salary.
The effect of communication is particularly revealing of the difference between constant-sum and variable-sum games. In constant-sum games it never helps a player to give an adversary information, and it never hurts a player to learn an opponent’s optimal strategy (pure or mixed) in advance. However, these properties do not necessarily hold in variable-sum games. Indeed, a player may want an opponent to be well-informed. In a labour-management dispute, for example, if the labour union is prepared to strike, it behooves the union to inform management and thereby possibly achieve its goal without a strike. In this example, management is not harmed by the advance information (it, too, benefits by avoiding a costly strike). In other variable-sum games, knowing an opponent’s strategy can sometimes be disadvantageous. For example, a blackmailer can only benefit if he first informs his victim that he will harm him—generally by disclosing some sensitive and secret details of the victim’s life—if his terms are not met. For such a threat to be credible, the victim must fear the disclosure and believe that the blackmailer is capable of executing the threat. (The credibility of threats is a question that game theory studies.) Although a blackmailer may be able to harm a victim without any communication taking place, a blackmailer cannot extort a victim unless he first adequately informs the victim of his intent and its consequences. Thus, the victim’s knowledge of the blackmailer’s strategy, including his ability and will to carry out the threat, works to the blackmailer’s advantage.
Cooperative versus noncooperative games
Communication is pointless in constant-sum games because there is no possibility of mutual gain from cooperating. In variable-sum games, on the other hand, the ability to communicate, the degree of communication, and even the order in which players communicate can have a profound influence on the outcome.
In the variable-sum game shown in , each matrix entry consists of two numbers. (Because the combined wealth of the players is not constant, it is impossible to deduce one player’s payoff from the payoff of the other; consequently, both players’ payoffs must be given.) The first number in each entry is the payoff to the row player (player A), and the second number is the payoff to the column player (player B).
In this example it will be to player A’s advantage if the game is cooperative and to player B’s advantage if the game is noncooperative. Without communication, assume each player applies the “sure-thing” principle: it maximizes its minimum payoff by determining the minimum it will receive whatever its opponent does. Thereby, A determines that it will do best to choose strategy I no matter what B does: if B chooses i, A will get 3 regardless of what A does; if B chooses ii, A will get 4 rather than 3. B similarly determines that it will do best to choose i no matter what A does. Selecting these two strategies, A will get 3 and B will get 4 at (3, 4).
In a cooperative game, however, A can threaten to play II unless B agrees to play ii. If B agrees, its payoff will be reduced to 3 while A’s payoff will rise to 4 at (4, 3); if B does not agree and A carries out its threat, A will neither gain nor lose at (3, 2) compared to (3, 4), but B will get a payoff of only 2. Clearly, A will be unaffected if B does not agree and thus has a credible threat; B will be affected and obviously will do better at (4, 3) than at (3, 2) and should comply with the threat.
Sometimes both players can gain from the ability to communicate. Two pilots trying to avoid a midair collision clearly will benefit if they can communicate, and the degree of communication allowed between them may even determine whether or not they will crash. Generally, the more two players’ interests coincide, the more important and advantageous communication becomes.
The solution to a cooperative game in which players have a common goal involves coordinating the players’ decisions effectively. This is relatively straightforward, as is finding the solution to constant-sum games with a saddlepoint. For games in which the players have both common and conflicting interests—in other words, in most variable-sum games, whether cooperative or noncooperative—what constitutes a solution is much harder to define and make persuasive.
The Nash solution
Although solutions to variable-sum games have been defined in a number of different ways, they sometimes seem inequitable or are not enforceable. One well-known cooperative solution to two-person variable-sum games was proposed by the American mathematician John F. Nash, who received the Nobel Prize for Economics in 1994 for this and related work he did in game theory.
Given a game with a set of possible outcomes and associated utilities for each player, Nash showed that there is a unique outcome that satisfies four conditions: (1) The outcome is independent of the choice of a utility function (that is, if a player prefers x to y, the solution will not change if one function assigns x a utility of 10 and y a utility of 1 or a second function assigns the values of 20 and 2). (2) Both players cannot do better simultaneously (a condition known as Pareto-optimality). (3) The outcome is independent of irrelevant alternatives (in other words, if unattractive options are added to or dropped from the list of alternatives, the solution will not change). (4) The outcome is symmetrical (that is, if the players reverse their roles, the solution will remain the same, except that the payoffs will be reversed).
In some cases the Nash solution seems inequitable because it is based on a balance of threats—the possibility that no agreement will be reached, so that both players will suffer losses—rather than a “fair” outcome. When, for example, a rich person and a poor person are to receive $10,000 provided they can agree on how to divide the money (if they fail to agree, they receive nothing), most people assume that the fair solution would be for each person to get half, or even that the poor person should get more than half. According to the Nash solution, however, there is a utility for each player associated with all possible outcomes. Moreover, the specific choice of utility functions should not affect the solution (condition 1) as long as they reflect each person’s preferences. In this example, assume that the rich person’s utility is equal to one-half the money received and that the poor person’s utility is equal to the money received. These different functions reflect the fact that additional income is more precious to the poor person. Under the Nash solution, the threat of reaching no agreement induces the poor person to accept one-third of the $10,000, giving the rich person two-thirds. In general, the Nash solution finds an outcome such that each player gains the same amount of utility.