RuleML+RR 2026

General information

The RuleML+RR industry track welcomes papers describing original industrial advances and application achievements in all areas of Rules and Reasoning-based technologies. We are interested in experiences from practitioners when applying rules to industries such as cybersecurity, data-driven decision making, healthcare, finance, energy, defense, aerospace, manufacturing, logistics, transportation, autonomous systems, government and law, life sciences, smart cities, telecommunications, engineering, environmental management, agriculture, retail, education, real estate, media, entertainment, tourism, and other emerging fields. Submissions are invited on all facets of Rules and Reasoning, including efforts to bridge recent research innovations with practical applications and industrial challenges, with a strong focus on the interplay between reasoning techniques and machine learning. 

We encourage submissions on the following topics:

• Integration of Rules, Reasoning, and Advanced AI Technologies: Novel approaches combining declarative rules/reasoning with generative AI, LLMs, reasoning models, agentic systems, and multimodal capabilities for industrial applications. Examples include rules to steer LLMs for verifiable decision-making, agent orchestration in enterprise workflows, RAG-enhanced rule systems, tool-calling in autonomous agents, and neuro-symbolic methods.

• Rules and Reasoning for Knowledge Graphs, Ontologies, and Dynamic Knowledge Systems: Methods for constructing, augmenting, maintaining, and querying enterprise knowledge graphs/ontologies, with rules central to schema alignment, fusion, and validation. Emphasis on LLM-empowered Knowledge Graph (KG) construction, KG-based reasoning to improve LLM accuracy and reduce LLM hallucinations, dynamic knowledge memory for agentic/long-context systems, and multimodal KGs (e.g., text, images, video) for applications like healthcare diagnostics or supply-chain monitoring..

• Advanced Uses of Rules and Reasoning in Scalable Applications: Innovative deployments in large-scale systems, and human-understandable explanations. Special focus on agentic AI trends: heterogeneous architectures (e.g., frontier models for orchestration plus small/edge models for efficiency), cost-performance optimization in rule-augmented agents, autonomous decision agents in logistics/finance, and other important areas.

• Rules and Reasoning in Regulatory Technology (RegTech) and Responsible AI: Rule-based systems for automating compliance and policy interpretation, real-time monitoring, and reporting in evolving regulations (e.g., AI safety, data privacy). Encouraged integrations with NLP, ML, KGs, and LLMs for transparent, auditable solutions, including ethical aspects: fairness, bias mitigation, accountability, explainability in hybrid systems, and best practices for responsible declarative + generative AI in regulated industries.

• Emerging Applications and Experiences: Practical case studies showing rule technologies synergizing with 2026 AI trends (e.g., edge AI for on-device reasoning, sustainable/green AI via optimized declarative systems, declarative approaches in autonomous multi-agent environments).

Submission and publication

We welcome original submissions and will not consider previously published work, advertisements, or sales pitches. Industry Track submissions should be extended abstracts of 5–6 pages (including references).

Accepted papers will be published as part of CEUR proceedings and should be written in English following in the CEUR-WS.org style template CEURART (1-column variant), available at:

http://ceur-ws.org/Vol-XXX/CEURART.zip

and

https://www.overleaf.com/read/gwhxnqcghhdt 

Reviews will be done by the committee of members from both industry and academia. Submitted papers must be original contributions written in English. Please submit your paper via:

https://cmt3.research.microsoft.com/DAI2026/Track/5/Submission/Create 

Important dates

June 5th, 2026: Paper submission deadline 

July 3rd, 2026: Notification deadline

For each of these deadlines, a cut-off point of 23:59 AOE applies.

Organisation

Chairs
Povilas Daniušis, Neurotechnology and Vytautas Magnus University, Lithuania

Program Committee
Ioan Toma, Onlim GmbH, Austria

Robert David, Vienna University of Economics and Business, Austria

Juliana Küster Filipe Bowles, University of St Andrews, United Kingdom

Martin Giese, University of Oslo, Norway

Darius Plikynas, Vilnius University, Lithuania 

Shubham Anoop Juneja, Nexos AI, Lithuania
Rokas Jurevičius, Daedalean AI, Switzerland