In
game theory, the common ways to describe a game are the
normal form and the
extensive form. The graphical form is an
alternate compact representation of a game using the interaction among participants.
Consider a game with
players with
strategies each. We will represent the players as nodes in a graph in which each player has a
utility function
As a topic of economics, utility is used to model worth or value. Its usage has evolved significantly over time. The term was introduced initially as a measure of pleasure or happiness as part of the theory of utilitarianism by moral philosoph ...
that depends only on him and his neighbors. As the utility function depends on fewer other players, the graphical representation would be smaller.
Formal definition
A graphical game is represented by a graph
, in which each player is represented by a node, and there is an edge between two nodes
and
iff their utility functions are dependent on the strategy which the other player will choose. Each node
in
has a function
, where
is the degree of vertex
.
specifies the utility of player
as a function of his strategy as well as those of his neighbors.
The size of the game's representation
For a general
players game, in which each player has
possible strategies, the size of a normal form representation would be
. The size of the graphical representation for this game is
where
is the maximal node degree in the graph. If
, then the graphical game representation is much smaller.
An example
In case where each player's utility function depends only on one other player:
Image:GraphicalGameExample.png, The graphical form of the described game
The maximal degree of the graph is 1, and the game can be described as
functions (tables) of size
. So, the total size of the input will be
.
Nash equilibrium
Finding Nash equilibrium in a game takes exponential time in the size of the representation. If the graphical representation of the game is a tree, we can find the equilibrium in polynomial time. In the general case, where the maximal degree of a node is 3 or more, the problem is
NP-complete
In computational complexity theory, a problem is NP-complete when:
# it is a problem for which the correctness of each solution can be verified quickly (namely, in polynomial time) and a brute-force search algorithm can find a solution by tryin ...
.
Further reading
* Michael Kearns (2007)
Graphical Games. In
* Michael Kearns, Michael L. Littman and Satinder Singh (2001)
Graphical Models for Game Theory.
{{Game theory
Game theory
Graph theory