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Recent results have shown that the MCTS algorithm (a new, adaptive,randomized optimization algorithm) is effective in a remarkably diverse set ofapplications in Artificial Intelligence, Operations Research, and High EnergyPhysics. MCTS can find good solutions without domain dependent heuristics,using the UCT formula to balance exploitation and exploration. It has beensuggested that the optimum in the exploitation- exploration balance differs fordifferent search tree sizes: small search trees needs more exploitation; largesearch trees need more exploration. Small search trees occur in variations ofMCTS, such as parallel and ensemble approaches. This paper investigates thepossibility of improving the performance of Ensemble UCT by increasing thelevel of exploitation. As the search trees becomes smaller we achieve animproved performance. The results are important for improving the performanceof large scale parallelism of MCTS.

Ensemble UCT Needs High Exploitation