Monte-Carlo Simulation Adjusting

Nobuo Araki, Masakazu Muramatsu, Kunihito Hoki, Satoshi Takahashi

AAAI 2014 pp. 3094-3095

doi:10.1609/AAAI.V28I1.9084 /aaai/2014/araki2014aaai-monte/

Abstract

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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Cite

Text

Araki et al. "Monte-Carlo Simulation Adjusting." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I1.9084

Markdown

[Araki et al. "Monte-Carlo Simulation Adjusting." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/araki2014aaai-monte/) doi:10.1609/AAAI.V28I1.9084

BibTeX

@inproceedings{araki2014aaai-monte,
  title     = {{Monte-Carlo Simulation Adjusting}},
  author    = {Araki, Nobuo and Muramatsu, Masakazu and Hoki, Kunihito and Takahashi, Satoshi},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2014},
  pages     = {3094-3095},
  doi       = {10.1609/AAAI.V28I1.9084},
  url       = {https://mlanthology.org/aaai/2014/araki2014aaai-monte/}
}