Links
Ritsumeikan University Intelligent Computer Entertainment Lab (ICE Lab) Homepage
http://www.ice.ci.ritsumei.ac.jp/
FTGAIC Facebook
YouTube
Fighting Action Games (from Wikipedia)
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List of Related Publications by Other Groups (those by our group are shown after this list)
JaeYoung Moon, YouJin Choi, TaeHwa Park, JunDoo Choi, Jin-Hyuk Hong, Kyung-Joong Kim, "Diversifying dynamic difficulty adjustment agent by integrating player state models into Monte-Carlo tree search," Expert Systems with Applications, 11 pages, Volume 205, Nov. 2022, 117677.
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Inseok Oh, Seungeun Rho, Sangbin Moon, Seongho Son, Hyoil Lee, Jinyun Chung, "Creating Pro-Level AI for a Real-Time Fighting Game Using Deep Reinforcement Learning," IEEE Transactions on Games, vol. 14, no. 2, pp. 212-220, Jun. 2022. (mentioning previous work using FightingICE, but using B&S Arena Battles in their experiment)
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Faisal Waris, Robert G. Reynolds and Joonho Lee, "Evolving Deep Neural Networks with Cultural Algorithms for Real-Time Industrial Applications," International Journal of Semantic Computing, Vol. 16, No. 02, pp. 281-312, Mar. 2022.
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Hai Liang, Jiaqi Li, "A Study on the Agent in Fighting Games Based on Deep Reinforcement Learning", Mobile Information Systems, vol. 2022, Article ID 9984617, 8 pages, Jul. 2022. (mentioning previous work using FightingICE, but using Street Fighter V in their experiment)
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Chollakorn Nimpattanavong; Worawat Choensawat; Kingkarn Sookhanaphibarn, "Action Prediction of AI Bot in FightingICE by using Deep Learning Model," Proc. of the 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), pp. 259-262, Mar. 2022.
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John Paul Q. Tomas, Nathanael Jhonn R. Aguas, Angela N. De Villa, Jasmin Rose G. Lim, "Developing an Adaptive AI Agent using Supervised and Reinforcement Learning with Monte Carlo Tree Search in FightingICE," Proc. of the 4th International Conference on Computational Intelligence and Intelligent Systems (CIIS 2021), pp. 31-36, Nov. 2021.
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Dae-Wook Kim, Sung-Yun Park, Seong-il Yang, "Reusing Agent's Representations for Adaptation to Tuned-environment in Fighting Game," 2021 International Conference on Information and Communication Technology Convergence, pp. 1120-1124, October 20-22, 2021.
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江口雄貴, 藤井叙人, 片寄晴弘, "対戦型格闘ゲームにおけるゲームバランスの自動調整 (Automatic game balance adjustment in fighting games)," The 26th Game Programming Workshop 2021, pp. 15-19, November 13-14, 2021.
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Junjie H. Xu, Zhou Fang, Qihang Chen, Satoru Ohno, Pujana Paliyawan, "Fighting Game Commentator with Pitch and Loudness Adjustment Utilizing Highlight Cues," 2021 IEEE 10th Global Conference on Consumer Electronics, pp. 366-370, October 12-15, 2021.
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Junjie H. Xu, Yulin Cai, Zhou Fang, Pujana Paliyawan, "Promoting Mental Well-Being for Audiences in a Live-Streaming Game by Highlight-Based Bullet Comments," 2021 IEEE 10th Global Conference on Consumer Electronics, pp. 383-385, October 12-15, 2021.
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Rongqin Liang, Yuanheng Zhu, Zhentao Tang, Mu Yang and Xiaolong Zhu, "Proximal Policy Optimization with Elo-based Opponent Selection and Combination with Enhanced Rolling Horizon Evolution Algorithm," 2021 IEEE Conference on Games, August 17-20, 2021.
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Tianyu Chen, Florian Richoux, Javier M. Torres, Katsumi Inoue, "Interpretable Utility-based Models Applied to the FightingICE Platform," 2021 IEEE Conference on Games, August 17-20, 2021.
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Marcel Hagen Francke, "Mehrkriterielle Optimierung anhand von Evolutionären Algorithmen unter genauerer Betrachtung des SMS-EMOA," Bachelor Thesis (The Universität der Bundeswehr München), Jan 31, 2021.
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Man-Je Kim , Jun Suk Kim , Sungjin James Kim , Min-jung Kim , Chang Wook Ahn, "Genetic state-grouping algorithm for deep reinforcement learning," Expert Systems with Applications, 15 December 2020.
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Xenija Neufeld, "Long-Term Planning and Reactive Execution in Highly Dynamic Environments," Doctoral thesis, Otto-von-Guericke-Universität Magdeburg, Dec. 2020.
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Zhentao Tang, Yuanheng Zhu, Dongbin Zhao, and Simon M. Lucas, "Enhanced Rolling Horizon Evolution Algorithm with Opponent Model Learning," IEEE Transactions on Games, 2020.
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Deng Shida, Takeshi Ito, "Fighting game AI with dynamic difficulty adjustment to make it fun to play against," Proc. of the 25th Game Programming Workshop 2020, pp. 58-61, Nov. 2020. (in Japanese)
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Yuanheng Zhu ,Dongbin Zhao, "Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games," IEEE Transactions on Neural Networks and Learning Systems, Nov. 2020. (Early Access)
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Mohammad Farhan Ferdous, "Privacy Preservation Algorithms on Cryptography for AI as Human-like Robotic Player for Fighting Game Using Rule-Based Method," Cyber Defense Mechanisms, pp. 185-196. Sep. 2020.
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MJ Kim, JH Lee, CW Ahn, "Genetic Optimizing Method for Real-time Monte Carlo Tree Search Problem," Proc. of the 9 International Conference on Smart Media and Applications, Sep, 2020.
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Dae-Wook Kim, Sungyun Park and Seong-il Yang, "Mastering Fighting Game Using Deep Reinforcement Learning With Self-play," The 2020 IEEE Conference on Games (CoG 2020), Online, Aug. 24-27, 2020.
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Tomoki Kajinami and Yousuke Miyauchi, "Observer Interface Focused on Trends of Character Movement and Stamina in Fighting Games," The 2020 IEEE Conference on Games (CoG 2020), Online, Aug. 24-27, 2020.
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Faisal Waris and Robert Reynolds, "Neuro-Evolution Using Game-Driven Cultural Algorithms," GECCO '20: Proc. of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1857–1865, Jul. 2020.
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Eirik H. Skjærseth and Harald Vinje, "Evolutionary algorithms for generating interesting fighting game character mechanics," Master’s thesis, Norwegian University of Science and Technology, Jul. 2020.
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Steven Künzel & Silja Meyer-Nieberg, "Coping with opponents: multi-objective evolutionary neural networks for fighting games," Neural Computing and Applications, vol. 32, pp. 13885–13916, Mar. 2020.
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山岡 勇太, "CFR 法と強化学習法の格闘ゲーム人工知能への適用," 電気通信大学大学院修士論文，2020年3月．
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Haruto Sasaki, "Game AI Using Changes Caused by Selected Actions," Bachelor's Thesis (Extended Abstract), Hosei University, Mar. 2020. (in Japanese)
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Inseok Oh, Seungeun Rho, Sangbin Moon, Seongho Son, Hyoil Lee, Jinyun Chung, "Creating pro-level AI for a real-time fighting game using deep reinforcement learning," arXiv preprint, 2019.
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Man-Je Kim, Jun Suk Kim, and Donghyeon Le,"Integrating Agent Actions with Genetic Action Sequence Method," GECCO' 19 Proc. of the Genetic and Evolutionary Computation Conference Companion, Prague, Czech Republic, July 13-17 2019.
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Lam Gia Thuan, Doina Logofatu and Costin Badica, "A Hybrid Approach for the Fighting Game AI Challenge: Balancing Case Analysis and Monte Carlo Tree Search for the Ultimate Performance in Unknown Environment," Proc. of 20th Engineering Applications of Neural Networks conferenc (EANN 2019), pp. 139-150, May 24-26, 2019.
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Man-Je Kim and Chang Wook Ahn, "Hybrid fighting game AI using a genetic algorithm and Monte Carlo tree search," GECCO' 18 Proc. of the Genetic and Evolutionary Computation Conference Companion, Kyoto, Japan, pp. 129-130, July 15 - 19, 2018.
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Ivan Pereira Pinto and Luciano Reis Coutinho, "Hierarchical Reinforcement Learning with Monte Carlo Tree Search in Computer Fighting Game," IEEE Transactions on Games (Early Access, Date of Publication: 11 June 2018), doi:10.1109/TG.2018.2846028
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Wataru Kamegaki, Koichi Moriyama, Atsuko Mutoh, Nobuhiro Inuzuka, "Trade-off between search time and responsiveness of MCTS in a fighting video game," Proc. of the 32nd Annual Conference of the Japanese Society for Artificial Intelligence, 4 pages, Jun. 2018.(in Japanese)
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佐藤 直之, "多様な性質のゲームと用途のためのコンピュータプレイヤ拡張の研究," 北陸先端科学技術大学院大学博士論文，2018年3月．
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S. Demediuk, M. Tamassia, W. Raffe, F. Zambetta, F. Mueller, and X. Li, "Measuring player skill using dynamic difficulty adjustment," in Proc. of the Australasian Computer Science Week Multiconference ACSW'18, Brisbane, pp. 1-7, January 29 - 2 February 2018.
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Marco Tamassia, "Artificial Intelligence Techniques Towards Adaptive Digital Games," PhD Thesis, RMIT, Sep 2017.
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Xenija Neufeld, Sanaz Mostaghim, and Diego Perez-Liebana, "HTN fighter: Planning in a highly-dynamic game," Proc. of 2017 Computer Science and Electronic Engineering (CEEC 2017), Colchester, UK, pp. 189-194, Sep. 2017.
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Simon Demediuk, Marco Tamassia, William Raffe, Fabio Zambetta, Xiaodong Li and Florian Floyd Mueller, "Monte Carlo Tree Search Based Algorithms for Dynamic Difficulty Adjustment," Proc. of 2017 IEEE Conference on Computational Intelligence and Games (CIG 2017), New York City, USA, Aug. 22-25, 2017.
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Seonghun Yoon and Kyung-Joong Kim, "Deep Q Networks for Visual Fighting Game AI," Proc. of 2017 IEEE Conference on Computational Intelligence and Games (CIG 2017), New York City, USA, Aug. 22-25, 2017.
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Man-Je Kim and Kyung-Joong Kim, "Opponent Modeling based on Action Table for MCTS-based Fighting Game AI," Proc. of 2017 IEEE Conference on Computational Intelligence and Games (CIG 2017), New York City, USA, Aug. 22-25, 2017.
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Alan Robsion, "Neural Network AI for FightingICE," Senior Project Report, California Polytechnic State University, Jun. 2017.
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Alex Oses Laza, "Reinforcement Learning in Videogames," Polytechnic University of Catalonia (UPC) Final Project, May 2017.
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Duc Tang Tri Nguyen, "Supervised and Reinforcement Learning for Fighting Game AIs using Deep Convolutional Neural Network," Master Thesis, Japan Advanced Institute of Science and Technology, Mar. 2017.
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酒井 賢人, 森山 甲一, 武藤 敦子, 犬塚 信博, "決定木学習を利用した格闘ゲームにおける対戦相手の行動予測に基づく行動選択," 第79回全国大会講演論文集, pp. 1015-1016, 2017年3月．
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Nguyen Duc Tang Tri, Vu Quang and Kokolo Ikeda, "Optimized Non-visual Information for Deep Neural Network in Fighting Game," Proc. of 9th International Conference on Agents and Artificial Intelligence(ICAART 2017), Porto, Portugal, pp. 676-680, Feb. 2017.
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Giovanna Martinez-Arellano, Richard Cant and David Woods, "Creating AI Characters for Fighting Games using Genetic Programming," IEEE Transactions on Computational Intelligence and AI in Games, Dec. 2016.
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Teofebano Kristo, Nur Ulfa Maulidevi, "Deduction of fighting game countermeasures using Neuroevolution of Augmenting Topologies," Proc. of 2016 International Conference on Data and Software Engineering (ICoDSE), Denpasar, Indonesia, Oct. 2016. DOI: 10.1109/ICODSE.2016.7936127
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Ngoc Quang Vu, "Building a Strong Fighting Game Player," Master Thesis, Japan Advanced Institute of Science and Technology, Sep. 2016.
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Richard Konecny, "Modeling of fighting game players," Master Thesis,Utrecht University, Aug, 2016.
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Gianlucca L. Zuin, Yuri P. A. Macedo, Luiz Chaimowicz, Gisele L. Pappa, "Discovering Combos in Fighting Games with Evolutionary Algorithms," GECCO'16, pp. 277-284, July 20-24, 2016, Denver, CO, USA.
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N. Sato, S. Temsiririkkul, S. Sone. and K. Ikeda, "Adaptive Fighting Game Computer Player by Switching Multiple Rule-based Controllers," Proc. of the 3rd International Conferenceon Applied Computing and Information Technology (ACIT 2015), pp. 52-59, 2015.
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K. Majchrzak, J. Quadflieg, and G. Rudolph, "Advanced Dynamic Scripting for Fighting Game AI," Proc. of Entertainment Computing (ICEC 2015), pp. 86-99, 2015.
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K. Asayama, K. Moriyama, K. Fukui, and M. Numao, "Prediction as Faster Perception in a Real-time Fighting Video Game," Proc. the 2015 IEEE Conference on Computational Intelligence and Games (CIG 2015), pp. 517-522, 2015.
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Kazuki Asayama, Koichi Moriyama, Ken-ichi Fukui, Masayuki Numao, "Prediction of the Opponent’s Position and Action in a Fighting Video Game with the Linear Extrapolation and the k-Nearest Neighbor Method," Proc. of the 29th Annual Conference of the Japanese Society for Artificial Intelligence, 4 pages, May-Jun. 2015. (in Japanese)
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H. Park and K.J. Kim, "Learning to Play Fighting Game using Massive Play Data," Proc. of 2014 IEEE Conference on Computational Intelligence and Games (CIG 2014), Dortmund, Germany, pp. 458-459, August 26-29, 2014
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K. Moriyama, S.E. Ortiz Branco, M. Matsumoto, K. Fukui, S. Kurihara, M. Numao,"An Intelligent Fighting Videogame Opponent Adapting to Behavior Patterns of the User," IEICE TRANSACTIONS on Information and Systems, vol. E97-D, no. 4, pp. 842-851, 2014.
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Simardeep Singh Saini, "Mimicking human player strategies in fighting games using game artificial intelligence techniques," PhD Thesis, Loughborough University, Mar. 2014.
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S.S. Saini, C.W. Dawson, and P.W.H. Chung, "Mimicking Player Strategies in Fighting Games," Proc. of the 2011 IEEE International Games Innovation Conference (IGIC), pp. 44--47, 2011.
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S, Lueangrueangroj and V. Kotrajaras, "Real-time Imitation based Learning for Commercial Fighting Games," Proc. of Computer Games, Multimedia and Allied Technology 09, International Conference and Industry Symposium on Computer Games, Animation, Multimedia, IPTV, Edutainment and IT Security, 2009.
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B.H. Cho, S.H. Jung, Y.R. Seong, and H.R. Oh, "Exploiting Intelligence in Fighting Action Games using Neural Networks," IEICE Transactions on Information and Systems, vol. E89-D, no. 3, pp. 1249-1256, 2006.
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Please let us know any other papers related to fighting game AIs, regardless of using FightingICE, so that we can list them here.
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List of Related Publications by our Group
Ryota Ishii, Keita Fujimaki, Ruck Thawonmas, "Fighting-Game Gameplay Generation Using Highlight Cues," IEEE Transactions on Games, vol. 14, no. 3, pp. 533-538, Sept. 2022.
--- PDF file link ---(in case you cannot access PDF files on IEEE Explore click)
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Thai Nguyen, Xincheng Dai, Ibrahim Khan, Ruck Thawonmas and Hai V. Pham, "A Deep Reinforcement Learning Blind AI in DareFightingICE," Proc. of the 2022 IEEE Conference on Games, pp. 632-637, Aug. 21-24, 2022.
--- PDF file link ---(in case you cannot access PDF files on IEEE Explore click)
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Ibrahim Khan, Thai Van Nguyen, Xincheng Dai, Ruck Thawonmas, "DareFightingICE Competition: A Fighting Game Sound Design and AI Competition," Proc. of the 2022 IEEE Conference on Games, pp. 478-485, Aug. 21-24, 2022.
--- PDF file link ---(in case you cannot access PDF files on IEEE Explore click)
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Pujana Paliyawan, Kingkarn Sookhanaphibarn, Worawat Choensawat and Ruck Thawonmas, "Towards Social Facilitation in Audience Participation Games: Fighting Game AIs whose Strength Depends on Audience Responses," The 2020 IEEE Conference on Games (CoG 2020), Online, Aug. 24-27, 2020.
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Junjie Xu, Tatsuki Toma, Zhou Fang, Pujana Paliyawan, Tomohiro Harada, Ruck Thawonmas, "Player Adaptive Motion Gaming AI for Health Promotion," Proc. of the 24th Game Programming Workshop 2019, pp. 221-226, Nov. 2019. (in Japanese)
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Ryota Ishii, Ruck Thawonmas, Tomohiro Harada, "An Analysis of Highlight-Oriented AI Using Fighting-Game Experience," Proc. of the 8th IEEE Global Conference on Consumer Electronics (GCCE 2019), Osaka, Japan, pp. 560-561, Oct. 15-18, 2019. (IEEE GCCE 2019 Excellent Poster Award Outstanding Prize)
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Ryota Ishii, Suguru Ito, Ruck Thawonmas, Tomohiro Harada, "A Fighting Game AI Using Highlight Cues for Generation of Entertaining Gameplay," The 2019 IEEE Conference on Games (CoG 2019), London, UK, Aug. 20-23, 2019.
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Takahiro Kusano, Yunshi Liu, Pujana Paliyawan, Ruck Thawonmas, Tomohiro Harada, "Motion Gaming AI using Time Series Forecasting and Dynamic Difficulty Adjustment," The 2019 IEEE Conference on Games (CoG 2019), London, UK, Aug. 20-23, 2019.
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Pujana Paliyawan,Takahiro Kusano, and Ruck Thawonmas, "Motion Recommender for Preventing Injuries During Motion Gaming," IEEE Access, vol.7, pp. 7977-7988. 2019, doi:10.1109/ACCESS.2018.2889166--------------------------------------------------------------------------------------------------------------------
Ryota Ishii, Suguru Ito, Ruck Thawonmas and Tomohiro Harada, "An Analysis of Fighting Game AIs Having a Persona," Proc. of the 7th IEEE Global Conference on Consumer Electronics (GCCE 2018), Nara, Japan, pp. 558-559, Oct. 9-11, 2018.
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Yoshina Takano, Suguru Ito, Tomohiro Harada, Ruck Thawonmas, "Utilizing Multiple Agents for Decision Making in a Fighting Game," Proc. of the 7th IEEE Global Conference on Consumer Electronics (GCCE 2018), Nara, Japan, pp. 562-563, Oct. 9-11, 2018.
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Yoshina Takano, Wenwen Ouyangy, Suguru Ito, Tomohiro Harada and Ruck Thawonmas, "Applying Hybrid Reward Architecture to a Fighting Game AI," Proc. of 2018 IEEE Conference on Computational Intelligence and Games (CIG 2018), Maastricht, The Netherlands, pp. 433-436, Aug. 14-17. 2018.
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Ryota Ishii, Suguru Ito, Makoto Ishihara, Tomohiro Harada and Ruck Thawonmas, "Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas," Proc. of 2018 IEEE Conference on Computational Intelligence and Games (CIG 2018), Maastricht, The Netherlands, pp. 54-61, Aug. 14-17. 2018.
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Makoto Ishihara, Suguru Ito, Ryota Ishii, Tomohiro Harada and Ruck Thawonmas, "Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors," Proc. of 2018 IEEE Conference on Computational Intelligence and Games (CIG 2018), Maastricht, The Netherlands, pp. 46-53, Aug. 14-17. 2018.
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Kazuki Mori, Suguru Ito, Tomohiro Harada, Ruck Thawonmas, and Kyung-Joong Kim, "Feature Extraction of Gameplays for Similarity Calculation in Gameplay Recommendation," Proc. of 2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IEEE IWCIA2017), Hiroshima, Japan, pp. 171-176, Nov. 11-12, 2017.
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Jorge Arturo Moran Bravo, Pujana Paliyawan, Tomohiro Harada and Ruck Thawonmas, "Intelligent Assistant for Providing Instructions and Recommending Motions During Full-body Motion Gaming," Proc. of the 6th IEEE Global Conference on Consumer Electronics (GCCE 2017), Aichi, Japan, pp. 342-343, Oct. 24-27, 2017. (IEEE GCCE 2017 Outstanding Demo! Award)
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Takahiro Kusano, Pujana Paliyawan, Tomohiro Harada and Ruck Thawonmas Thawonmas, "Towards Adaptive Motion Gaming AI with Player's Behavior Modeling for Health Promotion," Proc. of the 6th IEEE Global Conference on Consumer Electronics (GCCE 2017), Aichi, Japan, pp. 270-271, Oct. 24-27, 2017.
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Suguru Ito, Makoto Ishihara, Marco Tamassia, Tomohiro Harada, Ruck Thawonmas, and Fabio Zambetta, "Procedural Play Generation According to Play Arcs Using Monte-Carlo Tree Search," Proc. of the 18th International Conference on Intelligent Games and Simulation (GAME-ON'2017), Carlow, Ireland, pp. 67-71, Sep. 6-8, 2017.
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Kazuki Mori, Ayumu Shinya, Tomohiro Harada, and Ruck Thawonmas, "Feature Extraction of Game Plays for Procedural Play Generation," Proc. of 2017 NICOGRAPH International, Kyoto, Japan, pp. 86, Jun. 2-3, 2017.
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Suguru Ito, Makoto Ishihara, Tomohiro Harada, and Ruck Thawonmas, "Automatic Generation of Game Plays Considering the Play Arc by the AI in a Fighting Game," Proc. of 2017 NICOGRAPH International, Kyoto, Japan, pp. 87, Jun. 2-3, 2017.
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Takahiro Kusano, Pujana Paliyawan,Tomohiro Harada, and Ruck Thawonmas, "Analysis of Relationship Between the Player's Behavior Change and the Effectiveness of a Health Promotion AI," Proc. of 2017 NICOGRAPH International, Kyoto, Japan, pp. 92, Jun. 2-3, 2017.
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Pujana Paliyawan, Takahiro Kusano, Yuto Nakagawa, Tomohiro Harada, Ruck Thawonmas, "Health Promotion AI for Full-body Motion Gaming," 2017 AAAI Spring Symposium Series (Well-Being AI: From Machine Learning to Subjective Oriented Computing), San Francisco, USA, pp. 720-725, Mar. 27-29, 2017.
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Pujana Paliyawan and Ruck Thawonmas, "UKI: Universal Kinect-type-controller by ICE Lab," Software: Practice and Experience, Jan. 2017. DOI: 10.1002/spe.2474.
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Makoto Ishihara, Taichi Miyazaki, Tomohiro Harada, and Ruck Thawonmas, "Analysis of Effects of AIs and Interfaces to Players' Enjoyment in Fighting Games," IPSJ Journal, vol. 57, no. 11, pp. 1414-1425, Nov. 2016. (in Japanese)
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Makoto Ishihara, Taichi Miyazaki, Chun Yin Chu, Tomohiro Harada, and Ruck Thawonmas, "Applying and Improving Monte-Carlo Tree Search in a Fighting Game AI," Proc. of the 13th International Conference on Advances in Computer Entertainment Technology (ACE 2016), Osaka, Japan, Nov. 9-12, 2016. DOI: http://dx.doi.org/10.1145/3001773.3001797
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Pujana Paliyawan and Ruck Thawonmas, "Towards Ergonomic Exergaming," Proc. of the 5th IEEE Global Conference on Consumer Electronics (GCCE 2016), Kyoto, Japan, pp. 321-322, Oct. 11-14, 2016.
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Shubu Yoshida, Makoto Ishihara, Taichi Miyazaki, Yuto Nakagawa, Tomohiro Harada, and Ruck Thawonmas, "Application of Monte-Carlo Tree Search in a Fighting Game AI," Proc. of the 5th IEEE Global Conference on Consumer Electronics (GCCE 2016), Kyoto, Japan, pp. 623-624, Oct. 11-14, 2016.
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Yasutomo Kanetsuki, Ruck Thawonmas, and Susumu Nakata, "Optimization and Simplification of Dynamic Scripting with Evolution Strategy and Fuzzy Control in a Fighting Game AI," Proc. of the 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE 2015), Osaka, Japan, pp. 330-331, Oct. 27-30, 2015.
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Pujana Paliyawan, Kingkarn Sookhanaphibarn, Worawat Choensawat, and Ruck Thawonmas, "Towards Universal Kinect Interface for Fighting Games," Proc. of the 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE 2015), Osaka, Japan, pp. 332-333, Oct. 27-30, 2015.
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Makoto Ishihara, Taichi Miyazaki, Pujana Paliyawan, Chun Yin Chu,Tomohiro Harada, and Ruck Thawonmas, "Investigating Kinect-based Fighting Game AIs That Encourage Their Players to Use Various Skills," Proc. of the 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE 2015), Osaka, Japan, pp. 334-335, Oct. 27-30, 2015.
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Yuto Nakagawa, Kaito Yamamoto, Chu Chun Yin, Tomohiro Harada, and Ruck Thawonmas, "Predicting the Opponent's Action Using the k-Nearest Neighbor Algorithm and a Substring Tree Structure," Proc. of the 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE 2015), Osaka, Japan, pp. 533-534, Oct. 27-30, 2015.
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Pujana Paliyawana, Kingkarn Sookhanaphibarna, Worawat Choensawata, and Ruck Thawonmas, "Body Motion Design and Analysis for Fighting Game Interface," Proc. of 2015 IEEE Conference on Computational Intelligence and Games (CIG 2015), Tainan, Taiwan, pp. 360-367, Aug. 30 - Sep. 2, 2015.
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Kaito Yamamoto, Syunsuke Mizuno, and Ruck Thawonmas, "Proposal and Evaluation of an Automatic Analysis Method using StGA for Strategic Diversity in Action Games," IPSJ Journal, vol. 55, no. 11, pp. 2328-2335, Nov. 2014. (in Japanese)
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Yuto Nakagawa, Kaito Yamamoto, and Ruck Thawonmas, "Online Adjustment of the AI's Strength in a Fighting Game Using the k-Nearest Neighbor Algorithm and a Game Simulator," Proc. of the 3rd IEEE Global Conference on Consumer Electronics (GCCE 2014), Tokyo, Japan, pp. 494-495, Oct. 7-10, 2014. (IEEE GCCE 2014 Undergraduate Paper Award)
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Kaito Yamamoto, Syunsuke Mizuno, Chun Yin Chu and Ruck Thawonmas, "Deduction of Fighting-Game Countermeasures Using the k-Nearest Neighbor Algorithm and a Game Simulator," Proc. of 2014 IEEE Conference on Computational Intelligence and Games (CIG 2014), Dortmund, Germany, pp. 437-441, Aug. 26-29, 2014.
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Feiyu Lu, Kaito Yamamoto, Luis H. Nomura, Syunsuke Mizuno, YoungMin Lee, and Ruck Thawonmas, "Fighting Game Artificial Intelligence Competition Platform," Proc. of the 2nd IEEE Global Conference on Consumer Electronics (GCCE 2013), Tokyo, Japan, pp. 320-323, Oct. 1-4, 2013.
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Akinori Nakagawa, Tomoya Shibazaki, Shota Osaka, and Ruck Thawonmas, "Adjustment of Game Difficulty and Improvement of Action Variety in Fighting Action Games Using Neural Networks," Journal of Game Amusement Society, vol. 3, no. 1, pp. 35-40, 2009. (in Japanese)
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Syota Osaka, Ruck Thawonmas, and Tomoya Shibazaki, "Investigation of Various Online Adaptation Methods of Computer-Game AI Rulebase in Dynamic Scripting," CD-ROM Proc. of the 1st International Conference on Digital Interactive Media Entertainment and Arts (DIME-ARTS 2006), Bangkok, Thailand, Oct. 25-27, 2006.
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Ruck Thawonmas and Syota Osaka, "A Method for Online Adaptation of Computer-Game AI Rulebase," DVD Proc. of ACM SIGCHI International Conference on Advances in Entertainment Technology 2006 (ACE 2006), Hollywood, USA, Jun. 14-16, 2006.
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