The existence of stationary Markov perfect equilibria in stochastic games is shown in several contexts under a general condition called "  coarser transition kernels". These results include various earlier existence results on correlated equilibria, noisy stochastic games,  stochastic games with mixtures of constant transition kernels as special cases.  The minimality of the condition is illustrated. The results here also shed some new light on a recent example on the nonexistence of stationary equilibrium. The proofs are remarkably simple via establishing a new connection between stochastic games and conditional expectations of correspondences .
The existence of stationary Markov perfect equilibria in stochastic games is shown under a general condition called " (decomposable) coarser transition kernels". This result includes various earlier existence results on correlated equilibria, noisy stochastic games, and stochastic games with mixtures of constant transition kernels as special cases. A remarkably simple proof is provided via establishing a new connection between stochastic games and conditional expectations of correspondences. The minimality of our condition is demonstrated from a technical point of view. Our result also sheds some light on a recent example about the nonexistence of stationary equilibrium. New applications of stochastic games are presented as illustrative examples, including stochastic games with endogenous shocks and a stochastic dynamic oligopoly model .
D
in several contexts
A
(decomposable)
R
These results include
This result includes
A
and
A
A remarkably simple proof is provided via establishing a new connection between stochastic games and conditional expectations of correspondences.
R
the condition is illustrated. The results here also shed some new
our condition is demonstrated from a technical point of view. Our result also sheds some
R
on
about
R
The proofs are remarkably simple via establishing a new connection between stochastic games and conditional expectations of correspondences
New applications of stochastic games are presented as illustrative examples, including stochastic games with endogenous shocks and a stochastic dynamic oligopoly model