Knowledge representation and reasoning
We improve the understanding of the foundations on knowledge representation and its application to and integration with emerging artificial intelligence (AI) technologies.
Intelligent AI-driven computational systems usually rely on background or commonsense knowledge to draw appropriate conclusions and properly execute their tasks.
The Cardiff Knowledge Representation and Reasoning research group (CKRR) at Cardiff University aims to develop novel methods for capturing, modelling and reasoning about knowledge encoded in symbolic or sub-symbolic forms.
We also have a particular interest in research that crosses the boundaries of various AI fields, including neuro-symbolic reasoning, commonsense reasoning, and representation learning.
We aim to attract more:
- undergraduate and postgraduate students to the human-centered computing domain
- PhD students (funded and self-funded)
- post-doctorate and early-career researchers (and academics)
- funding from UKRI and industry.
We offer expertise in:
- ontology-enhanced systems
- knowledge graphs
- temporal and probabilistic reasoning
- neuro-symbolic reasoning
- non-monotonic reasoning
- belief change
- controlled natural language
- computational social choice.
- Booth, R. and Chandler, J. 2020. On strengthening the logic of iterated belief revision: proper ordinal interval operators. Artificial Intelligence 285 103289. (10.1016/j.artint.2020.103289)
- Chandler, J. and Booth, R. 2020. Revision by conditionals: from hook to arrow. Presented at: 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) Rhodes, Greece 12-18 September 2020.
- Gogacz, T. et al., 2020. On finite entailment of non-local queries in description logics. Presented at: 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) Rhodes, Greece 12-18 September 2020.
- Ibanez Garcia, Y. , Gutierrez Basulto, V. and Schockaert, S. 2020. Plausible reasoning about EL-Ontologies using concept interpolation. Presented at: 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) Rhodes, Greece 12-18 September 2020.
- Singleton, J. and Booth, R. 2020. An axiomatic approach to truth discovery. Presented at: Nineteenth International Conference on Autonomous Agents and Multi-Agent Systems Auckland, New Zealand 9-13 Mar 2020. , pp.-. (10.5555/3398761.3399058)
- Gutierrez Basulto, V. and Schockaert, S. 2018. From knowledge graph embedding to ontology embedding? An analysis of the compatibility between vector space representations and rules. Presented at: 16th International Conference on Principles of Knowledge Representation and Reasoning Tempe, Arizona 27 Oct - 2 Nov 2018.
- Dubois, D. , Prade, H. and Schockaert, S. 2017. Generalized possibilistic logic: foundations and applications to qualitative reasoning about uncertainty. Artificial Intelligence 252 , pp.139-174. (10.1016/j.artint.2017.08.001)
Recent and ongoing projects
Project name: Non-Classical Reasoning for Enhanced Ontology-based Semantic Technologies 2019-21
Principal investigator: Richard Booth, Ivan Varzinczak (Université d’Artois, France)
Funded by: Royal Society/CNRS
Project name: A Unifying Quantitative Framework for Deduplication and Repairing Data in Ontology- Enhanced Systems 2020-2022
Principal investigators: Víctor Gutiérrez-Basulto, Meghyn Bienvenu (CNRS, Labri University of Bordeaux)
Funded by: Royal Society