DBJAPANの皆様 お世話になっております。 京都工芸繊維大学の劉 云（Yun Liu）と申します。 このたび、KSE 2026（The 18th International Conference on Knowledge and Systems Engineering）の併設ワークショップとして、The 1st International Workshop on Multi-Agent and Knowledge-Driven Intelligent Systems and Applications (MAKIS 2026) を、2026年11月10日に金沢にて開催いたします。 MAKIS 2026では、マルチエージェントシステム、LLMエージェント、知識グラフ、知識拡張AI、データマイニング、情報検索、推薦システム、およびそれらの教育・科学・医療等への応用に関する幅広い研究発表を募集しております。 本ワークショップでは、ArchivalおよびNon-archivalの両方の投稿を受け付けております。進行中の研究、予備的な成果、既発表・採録済み研究、ポジションペーパー、システムデモ、萌芽的な研究アイデア等についても、Non-archival trackとしてご投稿いただけます。 皆様からのご投稿を心よりお待ちしております。また、ご関心をお持ちの研究者や学生の皆様にも本CFPをご共有いただけましたら幸いです。 【重要日程】 Paper Submission: September 18, 2026 Notification of Acceptance: October 5, 2026 Camera-ready Submission: October 15, 2026 Workshop: November 10, 2026 【開催地】 Kanazawa, Japan 【Workshop Website】 https://kse2026.kse-conferences.org/workshop-makis/ 【Submission】 https://cmt3.research.microsoft.com/KSE2026 Track: Workshop – MAKIS 2026 どうぞよろしくお願いいたします。 劉 云（Yun Liu） 京都工芸繊維大学 Email: liuyun(a)kit.ac.jp ------------------------------ Dear Colleagues, We are pleased to invite submissions to the 1st International Workshop on Multi-Agent and Knowledge-Driven Intelligent Systems and Applications (MAKIS 2026), to be held in conjunction with KSE 2026 on November 10, 2026, in Kanazawa, Japan. MAKIS 2026 aims to bring together researchers working on multi-agent systems, LLM agents, knowledge graphs, knowledge-enhanced AI, intelligent systems, data mining, information retrieval, recommender systems, and related applications. The workshop particularly welcomes research exploring how multiple intelligent agents can collaborate with structured and external knowledge to support reasoning, decision making, personalization, and human–AI interaction. Applications in education, scientific discovery, healthcare, recommendation, business intelligence, and other emerging areas are also welcome. Topics of interest include, but are not limited to: Multi-agent systems and agentic AI Multi-agent LLM systems Agent orchestration and coordination Role-based and heterogeneous agents Multi-agent planning and decision making Knowledge graphs and structured knowledge representation Knowledge-enhanced LLMs and agents Retrieval-augmented generation (RAG) Dynamic knowledge management Agent memory and knowledge sharing Adaptive and personalized intelligent systems Human–AI collaborative systems Data mining and knowledge discovery Intelligent recommender systems Reliable and controllable AI agents Hallucination detection and mitigation Efficient and scalable multi-agent systems AI for education and personalized learning Intelligent tutoring and collaborative learning systems AI for Science, healthcare, and other real-world applications Submission MAKIS 2026 welcomes both archival and non-archival submissions. Archival submissions should present original and unpublished research and will be considered for inclusion in the workshop proceedings, subject to the publication policy of KSE 2026. Non-archival submissions may include ongoing research, preliminary results, recently published or accepted work, position papers, system demonstrations, and emerging research ideas. Accepted non-archival submissions will be presented at the workshop but will not be included in the archival proceedings. Submission Format: Maximum 8 pages, IEEE conference template. Important Dates Paper Submission: September 18, 2026 Notification of Acceptance: October 5, 2026 Camera-ready Submission: October 15, 2026 Workshop: November 10, 2026 Workshop Website https://kse2026.kse-conferences.org/workshop-makis/ Submission https://cmt3.research.microsoft.com/KSE2026 Track: Workshop – MAKIS 2026 Organizers Qiang Ma, Kyoto Institute of Technology, Japan Nguyen Le Minh, Japan Advanced Institute of Science and Technology (JAIST), Japan Yijun Duan, Kyoto Institute of Technology, Japan Yun Liu, Kyoto Institute of Technology, Japan We would greatly appreciate it if you could share this CFP with colleagues and students who may be interested. We look forward to your submissions and participation in MAKIS 2026. Best regards, Yun Liu Kyoto Institute of Technology, Japan Email: liuyun(a)kit.ac.jp