The 1st International Workshop on Multi-Agent and Knowledge-Driven Intelligent Systems and Applications (MAKIS 2026)
Overview
Recent advances in large language models (LLMs), autonomous agents, and knowledge-enhanced artificial intelligence are transforming the way intelligent systems reason, collaborate, and interact with users. Rather than relying on a single monolithic model, multi-agent systems enable multiple agents with different capabilities, roles, and knowledge to collaborate, exchange information, and collectively solve complex tasks.
At the same time, knowledge graphs and other structured knowledge representations provide powerful mechanisms for organizing, retrieving, sharing, and controlling knowledge in intelligent systems. Integrating multi-agent intelligence with structured knowledge opens new opportunities for developing AI systems that are more collaborative, adaptive, interpretable, and capable of supporting complex real-world tasks.
The Workshop on Multi-Agent and Knowledge-Driven Intelligent Systems and Applications (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 encourages research that explores how multiple intelligent agents can collaborate with structured and external knowledge to support reasoning, decision making, personalization, and human–AI interaction.
MAKIS 2026 welcomes methodological advances, system development, empirical studies, and practical applications across domains including education, scientific discovery, healthcare, recommendation, business intelligence, and other emerging areas.
Why This Workshop?
MAKIS explores how multi-agent collaboration and structured knowledge can enable the next generation of intelligent systems. By bringing together advances in agent coordination, knowledge-driven reasoning, and real-world applications, the workshop aims to promote more adaptive, reliable, and capable AI systems.
Topics of Interest
Topics of interest include, but are not limited to:
Multi-Agent Intelligence
• Multi-agent systems and agentic AI
• Multi-agent LLM systems
• Agent orchestration and coordination
• Role-based and heterogeneous agents
• Agent communication and interaction
• Multi-agent planning and decision making
• Federated and distributed agent collaboration
• Mediated and coordinator-based agent systems
• Human–agent and agent–agent interaction
Knowledge Graphs and Knowledge-Driven Intelligence
• Knowledge graphs and structured knowledge representation
• Knowledge-enhanced large language models
• Knowledge-graph-enhanced agents
• Graph-based retrieval and reasoning
• Retrieval-augmented generation (RAG)
• Knowledge acquisition and integration
• Dynamic knowledge management
• Knowledge access and control
• Knowledge sharing among multiple agents
• Agent memory and structured memory
• Knowledge-grounded decision making
Intelligent Systems
• Adaptive and personalized intelligent systems
• Conversational and interactive AI systems
• Human–AI collaborative systems
• Intelligent information retrieval
• Intelligent recommender systems
• Decision-support systems
• Data mining and knowledge discovery systems
• Agentic workflows and AI assistants
• Context-aware intelligent systems
• Distributed and federated intelligent systems
• Intelligent knowledge management systems
Reliable and Efficient Intelligent Systems
• Hallucination detection and mitigation
• Agent verification and self-correction
• Consensus and disagreement modeling
• Confidence and uncertainty estimation
• Controllable agent behavior
• Explainable and interpretable agent systems
• Trustworthy and responsible AI
• Efficient multi-agent inference
• Resource-aware agent systems
• Scalable agent architectures
• Evaluation of multi-agent and knowledge-driven systems
Applications
• AI for education and personalized learning
• Intelligent tutoring and collaborative learning systems
• Scientific discovery and AI for Science
• Healthcare and biomedical applications
• Recommender systems and personalization
• Information retrieval and search
• Data mining and knowledge discovery
• Business and financial intelligence
• Social information systems
• Software engineering
• Smart cities and Internet of Things
• Industrial and enterprise applications
• Human–AI collaborative applications
• Other emerging applications of multi-agent and knowledge-driven AI
Paper Submission
MAKIS 2026 welcomes both archival and non-archival submissions, including original research papers, novel algorithms and methodologies, system demonstrations, empirical studies, benchmark and dataset papers, position and vision papers, industrial case studies, and emerging research ideas.
Archival submissions should present original and unpublished research relevant to the workshop topics. Papers should follow the IEEE conference template and the submission requirements of KSE 2026. Accepted archival papers will be included in the workshop proceedings, subject to the publication policy of KSE 2026.
Non-archival submissions may include ongoing work, preliminary results, recently published or accepted research, position papers, system demonstrations, and emerging ideas. Accepted non-archival submissions will be presented and discussed at the workshop but will not be included in the archival proceedings.
All submissions will be peer reviewed. Authors should indicate whether their submission is intended for the archival or non-archival track at the time of submission.
Submission Format: An 8-page (max) PDF manuscript conforming to IEEE template (Latex, Word): https://www.ieee.org/conferences/publishing/templates
Submission Link: https://cmt3.research.microsoft.com/KSE2026 (Track: Workshop – MAKIS 2026)
Important Dates
| Milestone | Date |
| Paper submission | September 18, 2026 |
| Notification of acceptance | October 05, 2026 |
| Camera-ready submission | October 15, 2026 |
| Workshop | November 10, 2026 |
Proceedings
Accepted papers will appear in the workshop proceedings, subject to the host conference’s publication policy. Selected authors may be invited to submit extended versions to a special issue of an international journal.
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
Contact
liuyun@kit.ac.jp