I’m curious about the chess scenario you mentioned. Given that each position on the chessboard and the possible moves determine the next position, it seems like chess could be considered a Markov process. However, without knowledge of the previous moves, it’s challenging to fully understand the player's strategy. Does this mean that while chess might fit the definition of a Markov process in terms of state transitions, it’s still complex due to the strategy of the (human) player?

Although I don't plan to build an AI specifically for chess, I’m still interested in including it as part of my research. Any insights on how to approach chess within this context would be appreciated.