Traveler's dilemma

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In game theory, the traveler's dilemma (sometimes abbreviated TD) is a type of non-zero-sum game in which two players attempt to maximize their own payoff, without any concern for the other player's payoff.

The game was formulated in 1994 by Kaushik Basu and goes as follows:[1][2]

An airline loses two suitcases belonging to two different travelers. Both suitcases happen to be identical and contain identical items. An airline manager tasked to settle the claims of both travelers explains that the airline is liable for a maximum of $100 per suitcase (he is unable to find out directly the price of the items), and in order to determine an honest appraised value of the antiques the manager separates both travelers so they can't confer, and asks them to write down the amount of their value at no less than $2 and no larger than $100. He also tells them that if both write down the same number, he will treat that number as the true dollar value of both suitcases and reimburse both travelers that amount. However, if one writes down a smaller number than the other, this smaller number will be taken as the true dollar value, and both travelers will receive that amount along with a bonus/malus: $2 extra will be paid to the traveler who wrote down the lower value and a $2 deduction will be taken from the person who wrote down the higher amount. The challenge is: what strategy should both travelers follow to decide the value they should write down?

One might expect a traveler's optimum choice to be $100; that is, the traveler values the antiques at the airline manager's maximum allowed price. Remarkably, and, to many, counter-intuitively, the traveler's optimum choice (in terms of Nash equilibrium) is in fact $2; that is, the traveler values the antiques at the airline manager's minimum allowed price.

For an understanding of this paradoxical result, consider the following rather whimsical proof.

  • Alice, having lost her antiques, is asked their value. Alice's first thought is to quote $100, the maximum permissible value.
  • On reflection, though, she realizes that her fellow traveler, Bob, might also quote $100. And so Alice changes her mind, and decides to quote $99, which, if Bob quotes $100, will pay $101.
  • But Bob, being in an identical position to Alice, might also think of quoting $99. And so Alice changes her mind, and decides to quote $98, which, if Bob quotes $99, will pay $100. This is greater than the $99 Alice would receive if both she and Bob quoted $99.
  • This cycle of thought continues, until Alice finally decides to quote just $2—the minimum permissible price.

Another proof goes as follows:

  • If Alice only wants to maximize her own payoff, choosing $99 trumps choosing $100. If Bob chooses any dollar value 2–98 inclusive, $99 and $100 give equal payoffs; if Bob chooses $99 or $100, choosing $99 nets Alice an extra dollar.
  • A similar line of reasoning shows that choosing $98 is always better for Alice than choosing $99. The only situation where choosing $99 would give a higher payoff than choosing $98 is if Bob chooses $100—but if Bob is only seeking to maximize his own profit, he will always choose $99 instead of $100.
  • This line of reasoning can be applied to all of Alice's whole-dollar options until she finally reaches $2, the lowest price.

The ($2, $2) outcome in this instance is the Nash equilibrium of the game. However, when the game is played experimentally, most participants select the value $100 or a value close to $100, including both those who have not thought through the logic of the decision and those who understand themselves to be making a non-rational choice.[citation needed] Furthermore, the travelers are rewarded by deviating strongly from the Nash equilibrium in the game and obtain much higher rewards than would be realized with the purely rational strategy. These experiments (and others, such as focal points) show that the majority of people do not use purely rational strategies, but the strategies they do use are demonstrably optimal. This paradox has led some to question the value of game theory in general, while others have suggested that a new kind of reasoning is required to understand how it can be quite rational ultimately to make non-rational choices. For instance, Capraro has proposed a model where humans do not act a priori as single agents but they forecast how the game would be played if they formed coalitions and then they act so as to maximize the forecast. His model fits the experimental data on the Traveler's dilemma and similar games quite well. [3]

One variation of the original traveler's dilemma in which both travelers are offered only two integer choices, $2 or $3, is identical mathematically to the Prisoner's dilemma and thus the traveler's dilemma can be viewed as an extension of prisoner's dilemma. The traveler's dilemma is also related to the game Guess 2/3 of the average in that both involve deep iterative deletion of dominated strategies in order to demonstrate the Nash equilibrium, and that both lead to experimental results that deviate markedly from the game-theoretical predictions.

Payoff matrix

The canonical payoff matrix is shown below (if only integer inputs are taken into account):

Canonical TD payoff matrix
100 99 98 97 3 2
100 100, 100 97, 101 96, 100 95, 99 1, 5 0, 4
99 101, 97 99, 99 96, 100 95, 99 1, 5 0, 4
98 100, 96 100, 96 98, 98 95, 99 1, 5 0, 4
97 99, 95 99, 95 99, 95 97, 97 1, 5 0, 4
3 5, 1 5, 1 5, 1 5, 1 3, 3 0, 4
2 4, 0 4, 0 4, 0 4, 0 4, 0 2, 2

Denoting by S=\{2,...,100\} the set of strategies available to both players and by F:S\times S\rightarrow {\mathbb  {R}} the payoff function of one of them we can write

F(x,y)=\min(x,y)+2\cdot \operatorname{sgn}(y-x)

(Note that the other player receives F(y,x) since the game is quantitatively symmetric).

References

  1. Kaushik Basu, "The Traveler's Dilemma: Paradoxes of Rationality in Game Theory"; American Economic Review, Vol. 84, No. 2, pp. 391–395; May 1994.
  2. Kaushik Basu,"The Traveler's Dilemma"; Scientific American Magazine, June 2007
  3. Capraro, V (2013). "A Model of Human Cooperation in Social Dilemmas". PLoS ONE 8 (8): e72427. doi:10.1371/journal.pone.0072427. 
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