I have this simple risk-like game I would like to develop an AI for.
Players move their
Units on the map and a simple fight resolution is done. There is a time constraint of 100ms for each round, the AI has complete information and fight resolution is deterministic but units move simultaneously each round.
As far as I understand the monte carlo approach, I need to copy the state of a current round and generate a tree with new game states, play it out randomly or do an evaluation.
zones keeps a list each
unit and they're moved around by storing
orders. They're kept in a dictionary for each turn and are applied at the end of the round. Deep copying this takes around 3ms and I guess is too slow to use effectively considering the time constraint. I was wondering if I could use this order-system to generate the tree faster by applying and undoing them, but I can't yet wrap my head around how I would do it.
This is my current class design:
How can I effectively add MCTS for this kind of game?