  This paper provides a complexity analysis for the game of dark Chinese chess
(a.k.a. "JieQi"), a variation of Chinese chess. Dark Chinese chess combines
some of the most complicated aspects of board and card games, such as long-term
strategy or planning, large state space, stochastic, and imperfect-information,
which make it closer to the real world decision-making problem and pose great
challenges to game AI. Here we design a self-play program to calculate the game
tree complexity and average information set size of the game, and propose an
algorithm to calculate the number of information sets.
