Concurrently search a game tree using minimax and AB pruning. Is that possible?
I'm going be competing in a board game AI competition at my school and am trying to come up with some ideas for concurrency to gain an edge. I will most likely be at a disadvantage because I will be implementing it in java and I understand c or c++ would be much faster.
It doesn't seem like you could just split the game tree in half because of the move ordering which should leave the best moves first and it seems that it would be difficult or maybe even impossible to communicate the current alpha/beta at a given depth. I'm going to be using transposition tables as well which would need to be synchronized.
Besides searching, is there something that a second thread could be doing which could aid in the search or provide some type of speed increase. Each AI will have 5 seconds to make a move and your program can be working while the opponent is thinking.
Any input, no matter how obscure, would be appreciated.
An overview can be found in the Chess Programming Wiki's parallel search article. Even if your actual game is not chess, many concepts will also apply. The site also covers sophisticated solutions for shared transposition tables.
However, when you don't have much time, I would not start with a parallel search. You are correct that parallelism can increase the strength of the search algorithm. It is very difficult to get it right, though, and the benefits are way lower than one would expect.
If you want to experiment with parallelism, go ahead. It is an interesting topic. However, if you just want to get the best results in a limited amount of time, I would recommend to stick with a sequential search, and instead focus on move ordering and correctness.
It is possible. You have to make communication between threads to have AB prunning help. Also, move ordering must be tweaked, it doesn't help if one thread has the best-rated moves to analyze while the others not.
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