Correlated equilibria are a generalization of Nash equilibria that permit agents to act in a correlated manner and can therefore, model learning in games. In this paper we define a special class of correlated equilibria that have hierarchical structure based on the factor graph. Such factor graph-based structural equilibria are more general than Nash equilibria and can model constrained dependencies than general correlated equilibria. We provide the numerical example for using noncooperative stochastic game model on the gene regulatory network under three solution concepts.