Helly metric
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In
game theory Game theory is the study of mathematical models of strategic interactions. It has applications in many fields of social science, and is used extensively in economics, logic, systems science and computer science. Initially, game theory addressed ...
, the Helly metric is used to assess the
distance Distance is a numerical or occasionally qualitative measurement of how far apart objects, points, people, or ideas are. In physics or everyday usage, distance may refer to a physical length or an estimation based on other criteria (e.g. "two co ...
between two strategies. It is named for Eduard Helly.


Definition

Consider a game \Gamma=\left\langle\mathfrak,\mathfrak,H\right\rangle, between player I and II. Here, \mathfrak and \mathfrak are the sets of pure strategies for players I and II respectively. The payoff function is denoted by H=H(\cdot,\cdot). In other words, if player I plays x\in\mathfrak and player II plays y\in\mathfrak, then player I pays H(x,y) to player II. The Helly metric \rho(x_1,x_2) is defined as : \rho(x_1,x_2)=\sup_\left, H(x_1,y)-H(x_2,y)\. The metric so defined is symmetric, reflexive, and satisfies the
triangle inequality In mathematics, the triangle inequality states that for any triangle, the sum of the lengths of any two sides must be greater than or equal to the length of the remaining side. This statement permits the inclusion of Degeneracy (mathematics)#T ...
.


Properties

The Helly metric measures distances between strategies, not in terms of the differences between the strategies themselves, but in terms of the consequences of the strategies. Two strategies are distant if their payoffs are different. Note that \rho(x_1,x_2)=0 does not imply x_1=x_2 but it does imply that the ''consequences'' of x_1 and x_2 are identical; and indeed this induces an equivalence relation. If one stipulates that \rho(x_1,x_2)=0 implies x_1=x_2, then the topology so induced is called the natural topology. The metric on the space of player II's strategies is analogous: : \rho(y_1,y_2)=\sup_\left, H(x,y_1)-H(x,y_2)\. Note that \Gamma thus defines ''two'' Helly metrics: one for each player's strategy space.


Conditional compactness

Recall the definition of \epsilon-net: A set X_\epsilon is an \epsilon-net in the space X with metric \rho if for any x\in X there exists x_\epsilon\in X_\epsilon with \rho(x,x_\epsilon)<\epsilon. A metric space P is conditionally compact (or precompact), if for any \epsilon>0 there exists a ''finite'' \epsilon-net in P. Any game that is conditionally compact in the Helly metric has an \epsilon-optimal strategy for any \epsilon>0. fMoreover, if the space of strategies for one player is conditionally compact, then the space of strategies for the other player is conditionally compact (in their Helly metric).


References

* Game theory {{gametheory-stub