I could be wrong here, but from my reading of the source this doesn't look like an A* search algorithm. For starters, the search space is nondeterministic, and

I could be wrong here, but from my reading of the source this doesn't look like an A* search algorithm. For starters, the search space is nondeterministic, and since you can only explore in one direction, you're not really performing a search space exploration as much as choosing a direction and going with it. Secondly, the implementation doesn't perform the combination of current state score and proposed state score that lies at the heart of the A* algorithm. Instead it takes the current state for granted (which, again, it must given the inability to backtrack) and chooses the available move with the largest score. Thirdly, and I'm reaching a little here, I can't find any place where any heuristic is used to optimize search performance by pruning the search tree. The search space is brute forced on each iteration, and the entire tree is scored. At the expense of seeming pedantic I suggest this is a greedy play algorithm rather than A*. You can be even more precise and call it a single-ply minimax. Now that that's out of the way, I should temper my criticism with the fact that this implementation works. It's not algorithmically complicated because it doesn't have to be. It doesn't use any of the typical performance tricks because it doesn't need to. What it lacks in sophistication it makes up in "good enough."