AAAI Publications, Twenty-Eighth AAAI Conference on Artificial Intelligence

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Monte-Carlo Simulation Adjusting
Nobuo Araki, Masakazu Muramatsu, Hoki Kunihito, Satoshi Takahashi

Last modified: 2014-06-21


In this paper, we propose a new learning method sim- ulation adjusting that adjusts simulation policy to im- prove the move decisions of the Monte Carlo method. We demonstrated simulation adjusting for 4 × 4 board Go problems. We observed that the rate of correct an- swers moderately increased.



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