Publications

Journal

•  Shiyao Ding and Takayuki Ito, Pattern-Based Meta Graph Neural Networks for Argument Classifications, IEICE Transaction on Information and Systems,2024.

• Yihan Dong, Shiyao Ding, and Takayuki Ito. An Automated Multi-phase Facilitation Agent based on LLM. IEICE Transaction on Information and Systems, 2024.

• Shiyao Ding and Donghui Lin, “Multi-Agent Reinforcement Learning for Cooperative Task Offloading in Distributed Edge Cloud Computing,” IEICE Transactions on Information and Systems, E105-D(5), pp.936-945, 2022. [DOI]

• Shiyao Ding and Donghui Lin, “Deep Coalitional Q-learning for Dynamic Coalition Formation in Edge Computing,” IEICE Transactions on Information and Systems, E105-D(5), pp.846-872, 2022. [DOI]

International Conference 

•  Shiyao Ding and Takayuki Ito. MineLlama: Llama with Retrieval-Augmented Generation as A Decision Maker in Minecraft, 22nd International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2024), Spain, 26th-28th June, 2024.(to appear)

• Kazuhito Mori,  Shiyao Ding, Susmu Ohnuma, Yume Souma and Takayuki Ito, “Automatic Evaluation of Discussion Quality Using LLM Data Augmentation”, ACM Collective Intelligence (ACM CI 2024),Boston, MA, June 26-29, 2024.06.26-29. (to appear)

• Moeka Nomura, Takayuki Ito, Shiyao Ding,Towards Collaborative Brainstorming among Humans and AI Agents: An Implementation of the IBIS-based Brainstorming Support System with Multiple AI Agents, ACM Collective Intelligence (ACM CI 2024),Boston, MA, June 26-29, 2024.06.26-29. (to appear)

• Shiyao Ding and Takayuki Ito, Self-Agreement: A Framework for Fine-tuning Language Models to Find Agreement among Diverse Opinions, The 20th Pacific International Conference on Artificial Intelligence (PRICAI 2023), November 17-19, 2023, Jakarta, Indonesia. 

• Shiyao Ding and Takayuki Ito, A Deep Reinforcement Learning Based Facilitation Agent for Consensus Building among Multi-Round Discussions, The 20th Pacific International Conference on Artificial Intelligence (PRICAI 2023), November 17-19, 2023, Jakarta, Indonesia.

• Shiyao Ding, Hideki Aoyama and Donghui Lin, MARL4DRP: Benchmarking Cooperative Multi-Agent Reinforcement Learning Algorithms for Drone Routing Problems, The 20th Pacific International Conference on Artificial Intelligence (PRICAI 2023), November 17-19, 2023, Jakarta, Indonesia. 

• Shiyao Ding and Takayuki Ito. Graph Convolutional Networks for Link Prediction in Argument Structure Extraction. The 17th International Conference on Knowledge, Information, and Creativity Support Systems, November 2022. 

• Shiyao Ding, Hideki Aoyama, and Donghui Lin, “Combining Multiagent Reinforcement Learning and Search Method for Drone Delivery on a Non-Grid Graph,” 20th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2022), L’Aquila, Italy, July, 2022.

• Shiyao Ding, Donghui Lin, and Xin Zhou, “Graph Convolutional Reinforcement Learning for Dependent Task Allocation in Edge Computing,” The 5th IEEE International Conference on Agents (IEEE ICA 2021), pp.25-30, Japan, December, 2021. [DOI] (Best Student Paper Award)

• Shiyao Ding. Multi-Agent Reinforcement Learning for Task Allocation in Cooperative Edge Cloud Computing. In The International Conference on Service-Oriented Computing (ICSOC 2021), PhD Symposium, November 2021.

• Shiyao Ding and Donghui Lin, “A Coalitional Markov Decision Process Model for Dynamic Coalition Formation among Agents,” The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2020), pp.308-315, Melbourne, Australia, December 2020. [DOI]

• Bowen Wei, Donghui Lin, and Shiyao Ding. “A Constraint-based Approach to Edge Resource Allocation for Complex Event Processing,” The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2020), pp.526-531, Melbourne, Australia, December 2020. [DOI]

• Shiyao Ding and Donghui Lin, “Dynamic Task Allocation for Cost-Efficient Edge Cloud Computing,” The 17th IEEE International Conference on Services Computing (IEEE SCC 2020), pp.218-225, Beijing, China, October, 2020. [DOI]

Japan Domestic Conference 

• 丁世堯, 伊藤孝行,“大規模言語モデルはオープンワールドゲームにおける意思決定にいかに役立つか”第38回人工知能学会全国大会, 静岡県浜松市, 2024年5月28日～31日.

• 北河英己, 丁世堯, 伊藤孝行, “依存関係を持つ複数のゴールを達成するための強化学習エージェントの実装”, 情報処理学会第86回全国大会, 横浜市, 2024年3月15日-17日.

• 森 一仁, 丁世堯, 大沼 進, 相馬 ゆめ, 伊藤 孝行, “Discourse Quality Index (DQI)に基づく大規模言語モデルを用いた発言の自動分類”, 第４回電子情報通信学会 合意と共創研究会, 北海道, 2024年2月21日.

• 新居恵一郎, 蟻坂 竜太, 丁世堯, 伊藤 孝行, “日本語テキストの局所的な談話構造とその階層性に基づくグラフ化手法の提案”, 第４回電子情報通信学会 合意と共創研究会, 北海道, 2024年2月21日.

• 清水貴史, 丁世堯, 伊藤 孝行, “集団思考を防止するLLMエージェントの実装”, 第４回電子情報通信学会 合意と共創研究会, 北海道, 2024年2月21日.

• Yihan Dong, Shiyao Ding and Takayuki Ito. An Implementation of an Automated Facilitation Agent Promoting Inclusive Discussion, 熊本県熊本市, 第37回人工知能学会全国大会, 2023年6月6日〜9日

• 丁世堯, 伊藤孝行, How Large Language Models Can Benefit Consensus Building,第１回合意と共創（Consensus）研究会（口頭発表），電子情報通信学会，2023年3月20日.

• 丁世堯, 伊藤孝行, Graph convolutional networks for node classification in issue-based information systems, 情報処理学会第85回全国大会,東京都,2023年3月2日〜4日.

• Yihan Dong, Shiyao Ding, Jawad Haqbeen and Takayuki Ito. The Significant Factors that Affect the Accuracy on Classifying English IBIS Datasets, 情報処理学会第85回全国大会,東京都,2023年3月2日〜4日.

• 青山 秀紀, 丁 世堯, 林 冬惠, “ドローン配送計画最適化問題のための最短経路情報を利用したマルチエージェント強化学習,” 第36回 人工知能学会 全国大会, 3O3-GS-5, 京都, 16 Jun. 2022. [DOI]

• Shiyao Ding, Hideki Aoyama, and Donghui Lin, “Non-Grid Multiagent Pathfinding via Combining Learning-based Method and Search-based Method,” The 36th Annual Conference of the Japanese Society for Artificial Intelligence, 1S1-IS-3-02, Kyoto, Japan, 14 Jun. 2022. [DOI]

• Shiyao Ding, Hideki Aoyama, and Donghui Lin, “Combining Multiagent Reinforcement Learning and Discrete Event Modeling for Pathfinding on a Non-Grid Graph,” IEICE Technical Report, vol. 121, no. 157, SC2021-13, pp.13-17, Online, 27 Aug. 2021. [IEICE]