Tries to find a MPE by computing iteratively best replies

Returns a game object that contains the mpe. Use the function get_mpe to retrieve a data frame that describes the MPE.

rel_mpe(
  g,
  delta = g$param$delta,
  static.eq = NULL,
  max.iter = 100,
  tol = 1e-08,
  a.init.guess = NULL
)

Arguments

g	the game
delta	the discount factor
max.iter	maximum number of iterations
tol	we finish if payoffs in a subsequent iteration don't change by more than tol
a.init.guess	optionaly an initially guess of the action profiles. A vector of size nx (number of states) that describes for each state the integer index of the action profile. For a game g look at `g$ax.grid` to find the indeces of the desired action profiles.