- 著者
- Ihara Hiroyuki Imai Shunsuke Oyama Satoshi Kurihara Masahito
- 出版者
- IEEE
- 巻号頁・発行日
- pp.2182-2187, 2018
- 被引用文献数
- 1
Artificial intelligence has shown remarkable performance in perfect information games. However, it is still no match for human players when it comes to most imperfect information games. Information set Monte Carlo tree search (ISMCTS) has been developed to reduce the effects of strategy fusion caused by determinization of the imperfect information and demonstrated advantages over the conventional Monte Carlo tree search (MCTS) that uses determinization. Because ISMCTS has only been used for games with relatively simple structure, it is still unknown whether it works effectively for more complex games. In this study, we take Pok´emon as an example of a complex imperfect information game and implement a simulator to evaluate the effectiveness of ISMCTS. Experimental results show that ISMCTS outperforms the conventional MCTS that uses determinization.
- 著者
- Oyama Satoshi Baba Yukino Ohmukai Ikki Dokoshi Hiroaki Kashima Hisashi
- 出版者
- IEEE (Institute of Electrical and Electronics Engineers)
- 巻号頁・発行日
- pp.1-9, 2015
- 被引用文献数
- 2
Despite recent open data initiatives in many coun- tries, a significant percentage of the data provided is in non- machine-readable formats like image format rather than in a machine-readable electronic format, thereby restricting their usability. This paper describes the first unified framework for converting legacy open data in image format into a machine- readable and reusable format by using crowdsourcing. Crowd workers are asked not only to extract data from an image of a chart but also to reproduce the chart objects in spreadsheets. The properties of the reconstructed chart objects give their data structures including series names and values, which are useful for automatic processing of data by computer. Since results produced by crowdsourcing inherently contain errors, a quality control mechanism was developed that improves the accuracy of extracted tables by aggregating tables created by different workers for the same chart image and by utilizing the data structures obtained from the reproduced chart objects. Experimental results demonstrated that the proposed framework and mechanism are effective.