The last few years have witnessed a growing interest in AI methods that combine aspects of Machine Learning (ML) with insights and methods from the field of Knowledge Representation and Reasoning (KR). This trend is motivated by the clear complementarity of ML and KR. For instance, the popularity and success of ML based systems has put issues such as explainability, bias, fairness, sustainability, symbol grounding and so forth, firmly in the spotlight, and addressing these issues naturally leads to systems in which symbolic representations play a central role. On the other hand, ML also offers solutions for long-standing challenges in the field of KR, for instance related to efficient, neurally-guided, noise-tolerant and ampliative inference, knowledge acquisition, and the
limitations of symbolic representations. The synergy between ML and KR has the potential to lead to new advancements in fundamental AI challenges including, but not limited to, learning symbolic generalisations from raw (multi-modal) data, using knowledge to facilitate data-efficient learning, speeding up inference, supporting interpretability of learned outcomes and integration of symbolic planning and reinforcement learning.
This year, for the third time, KR2023 will host a special session on “Knowledge Representation and Machine Learning”, which aims at providing researchers and practitioners with a dedicated forum for the discussion of new ideas and research results at the intersection of these two fields. This special session will provide participants with the opportunity to make meaningful connections and develop a shared understanding of the challenges involved in developing innovative AI solutions that rely on a combination of insights and methods from ML and KR.
The Special Session on KR and ML at KR2023 invites submissions of papers that combine aspects of KR and ML research, including the use of KR methods for solving ML challenges (e.g. knowledge-guided or explainable learning), the use of ML methods for solving KR challenges (e.g. efficient inference, knowledge base completion), the integration of learning and reasoning at modeling or solving side, and the application of combined KR and ML approaches to solve real-world problems.
We welcome papers on a wide range of topics, including but not limited to:
Learning symbolic knowledge, such as ontologies and knowledge graphs, action theories, commonsense knowledge, spatial and temporal theories, preference models and causal models
Logic-based, logical and relational learning algorithms
Machine-learning driven reasoning algorithms
Statistical relational learning
Symbolic reinforcement learning
Learning symbolic abstractions from unstructured data
Expressive power of learning representations
Knowledge-driven natural language understanding and dialogue
Knowledge-driven decision making
Knowledge-driven intelligent systems for internet of things and cybersecurity
Architectures that combine data-driven techniques and formal reasoning
Submission Guidelines and Evaluation Criteria
The Special Session on KR and ML will allow contributions of both regular papers (9 pages) and short papers (4 pages), excluding
references, prepared and submitted according to the authors guidelines in the submission page.
The special session welcomes contributions that extend the state-of-the-art at the intersection of KR and ML. Therefore, KR-only or
ML-only submissions will not be accepted for evaluation in this special session.
Submissions will be rigorously peer reviewed by PC members who are active in KR and ML. Submissions will be evaluated on the basis of the originality, soundness, relevance and significance of the technical contribution, as well as the overall presentation quality.
Each submission should be in English and must be submitted electronically (in .pdf format) via EasyChair:
All dates are ‘Anywhere on Earth’, namely 23:59 UTC-12.
- Submission of title and abstract: March 3, 2023
- Paper submission deadline: March 14, 2023
- Author response period: May 1-3, 2023
- Author notification: May 18, 2023
- Camera-ready papers: June 9, 2023
- Conference: September 2-8, 2023
Tias Guns KU Leuven, Belgium
Luciano Serafini Fondazione Bruno Kessler, Italy