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IKEDA, Kokolo Professor, Director of International Research Center for Artificial Intelligence and Entertainment Science
Transdisciplinary Sciences, Information Science, Human Information Science, International Research Center for Artificial Intelligence and Entertainment Science
◆Degrees
Ph.D. Tokyo Institute of Technology
◆Professional Experience
: Associate at Kyoto University(2003), Assistant Professor at Kyoto University(2007)
◆Specialties
Intelligent informatics
◆Research Keywords
Strong/Entertaining/Educating Game AI, Machine Learning, Agent Simulation, Go, information education, 遺伝的アルゴリズム, 意思決定, ゲーム, 事例ベース推論, optimization, Artificial Intelligence, Artificial intelligence
◆Research Interests
Research on Computer GO Player using Evolution and Machine Learning



Game AI who can be the Rival or Teacher of Human Player
Many researches have been done for improving strength of game AI for especially classical games such as Go or Chess, and its strength is almost enough now. However game AI are still not rival or teacher of human player. For this purpose, game AI should be more natural, varied and well controlled by some strategies.

■Publications

◆Published Papers
More Human-Like Gameplay by Blending Policies from Supervised and Reinforcement Learning
Tatsuyoshi Ogawa, Chu-Hsuan Hsueh, Kokolo Ikeda
IEEE Transactions on Games, 1-13, 2024
Procedural Content Generation of Super Mario Levels Considering Natural Connection
SangGyu Nam, Chu-Hsuan Hsueh, Kokolo Ikeda
2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE), -, 2023
Graph Convolutional Networks for Turn-Based Strategy Games
Wanxiang Li, Houkuan He, Chu-Hsuan Hsueh, Kokolo Ikeda
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, -, 2022
Position control and production of various strategies for game of go using deep learning methods
Yuan Shi, Tianwen Fan, Wanxiang Li, Chu-Hsuan Hsueh, Kokolo Ikeda
Journal of Information Science and Engineering, 37, 3, 553-573, 2021
Imitating Agents in A Complex Environment by Generative Adversarial Imitation Learning
Wanxiang Li, Chu-Hsuan Hsueh, Kokolo Ikeda
2020 IEEE Conference on Games (CoG), -, 2020
◆Misc
Research on Strength Control Go AI Using Deep Learning Methods
SHI Yuan, FAN Tianwen, LI Wanxiang, 池田心
情報処理学会研究報告(Web), 2019, GI-41, Vol.2019‐GI‐41,No.9,1‐8 (WEB ONLY)-, 2019
不完全情報ゲーム『ガイスター』における2種の詰め問題の提案と考察
石井岳史, 川上直人, 橋本剛, 池田心
情報処理学会研究報告(Web), 2019, GI-41, Vol.2019‐GI‐41,No.19,1‐8 (WEB ONLY)-, 2019
連鎖構成力向上のための多様で面白いなぞぷよ提供法の提案
牧田光平, 池田心
情報処理学会研究報告(Web), 2019, GI-41, Vol.2019‐GI‐41,No.21,1‐8 (WEB ONLY)-, 2019
コンピューターゲームプレイヤにおける人間らしさの調査
テンシリリックン シラ, 高橋一幸, ナム サンギュ, 池田心
情報処理学会研究報告(Web), 2018, GI-40, Vol.2018‐GI‐40,No.7,1‐6 (WEB ONLY)-, 2018
Procedural Contents Generation of Rhythm Games for Self‐Training
LIANG Yubin, 池田心
情報処理学会研究報告(Web), 2018, GI-39, Vol.2018‐GI‐39,No.11,1‐7 (WEB ONLY)-, 2018
◆Books
進化技術ハンドブック = Handbook of evolutionary technology : computation and applications 第1巻 : 基礎編
分担執筆, 73-79, 近代科学社, 2010
◆Conference Activities & Talks
Human-like Computer Game Players
2018 ASEAN Workshop on Information Science and Technology, 2018
人間にとって乱数らしく見える疑似乱数の生成方法
平成30年度(2018)理工系情報学科・専攻協議会 総会・研究会, 2018
AIに人間の代わりは務まるか：楽しませる囲碁プログラムの研究より
平成28年度 ISP交流セミナー, 石川ハイテク交流センター, 2016
Artificial Intelligence in Computer Games: Not Only Strong, But Also Entertaining
JAIST Symposium on Advanced Science and Technology (JAIST-SAST 2015), JAIST, 2015
モンテカルロシミュレーションと並列探索 ―人智に迫る囲碁・将棋プログラム―」
JAISTシンポジウム2012, 富士ソフトアキバプラザ, 2012

■Teaching Experience

Game Informatics, Algorithms and Data Structures, ゲーム情報学持論, アルゴリズムとデータ構造

■Contributions to  Society

◆Academic Society Affiliations
Computer Go Forum, Information Processing Society of Japan, The Japanese Society for Evolutionary Computation, Japan Industrial Management Association, SICE

■Academic  Awards

・ 若手奨励賞 , IPSJ SIGGI , 2019
・ ベストポスター賞 , IPSJ SIGGI , 2018
・ 優秀発表賞 , エンターテイメントと認知科学研究ステーション , 2015