Author:
Oikawa Taishi,Hsueh Chu-Hsuan,Ikeda Kokolo
Publisher
Springer International Publishing
Reference19 articles.
1. De Kegel, B., Haahr, M.: Procedural puzzle generation: a survey. IEEE Trans. Games 12(1), 21–40 (2020). https://doi.org/10.1109/TG.2019.2917792
2. Demediuk, S., Tamassia, M., Raffe, W.L., Zambetta, F., Li, X., Mueller, F.: Monte Carlo tree search based algorithms for dynamic difficulty adjustment. In: 2017 IEEE Conference on Computational Intelligence and Games (CIG 2017), pp. 53–59. IEEE (2017). https://doi.org/10.1109/CIG.2017.8080415
3. Hirose, M., Ito, T., Matsubara, H.: Automatic composition of Tsume-shogi by reverse method. J. Jpn. Soc. Artif. Int. 13(3), 452–460 (1998)
4. Hunicke, R., Chapman, V.: AI for dynamic difficulty adjustment in games. In: AAAI-04 Workshop on Challenges in Game Artificial Intelligence, pp. 91–96. AAAI Press (2004)
5. Lecture Notes in Computer Science;K Ikeda,2015
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. On the Evaluation of Procedural Level Generation Systems;Proceedings of the 19th International Conference on the Foundations of Digital Games;2024-05-21
2. How fast can we play Tetris greedily with rectangular pieces?;Theoretical Computer Science;2024-04
3. Procedural Content Generation of Super Mario Levels Considering Natural Connection;2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE);2023-06-28
4. Procedural Maze Generation Considering Difficulty from Human Players’ Perspectives;Lecture Notes in Computer Science;2022