About
Adam is an Associate Professor Computer Science.
Dr Adam Wyner
Associate Professor
Computer Science
Research Links
Areas Of Expertise
- Artificial Intelligence and Law
- Natural Language Processing
- Argumentation
- Knowledge representation
- Knowledge acquisition
- Reasoning
- Semantic Web
- Knowledge graph
Publications
Research Highlights
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Bhattacharya, P., Paul, S., Ghosh, K., Ghosh, S., & Wyner, A. (2023). DeepRhole: deep learning for rhetorical role labeling of sentences in legal case documents. Artificial Intelligence and Law, 31(1), 53-90.
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Fawei, B., Pan, J., Kollingbaum, M., & Wyner, A. (2019). A Semi-automated Ontology Construction for Legal Question Answering. New Generation Computing, 37(4), 453-478.
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Bansky, P., Edelstein, E., Pan, J., & Wyner, A. (2020). A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. In Semantic Technology (pp. 226-241). Springer International Publishing.
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Edwards, J., Wintersberger, P., Clark, L., Rough, D., Doyle, P., Banks, V., Wyner, A., Janssen, C., & Cowan, B. (2021). CUI @ Auto-UI: Exploring the Fortunate and Unfortunate Futures of Conversational Automotive User Interfaces. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 186-189). ACM.
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Pan, J., Edelstein, E., Bansky, P., & Wyner, A. (2021). A Knowledge Graph Based Approach to Social Science Surveys. Data Intelligence, 3(4), 477-506.
All Research
Journal Articles
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Bhattacharya, P., Paul, S., Ghosh, K., Ghosh, S., & Wyner, A. (2023). DeepRhole: deep learning for rhetorical role labeling of sentences in legal case documents. Artificial Intelligence and Law, 31(1), 53-90.
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Pan, J., Edelstein, E., Bansky, P., & Wyner, A. (2021). A Knowledge Graph Based Approach to Social Science Surveys. Data Intelligence, 3(4), 477-506.
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Liepiņa, R., Sartor, G., & Wyner, A. (2020). Arguing about causes in law: a semi-formal framework for causal arguments. Artificial Intelligence and Law, 28(1), 69-89.
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Fawei, B., Pan, J., Kollingbaum, M., & Wyner, A. (2019). A Semi-automated Ontology Construction for Legal Question Answering. New Generation Computing, 37(4), 453-478.
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Strass, H., Wyner, A., & Diller, M. (2019). EMIL: Extracting Meaning from Inconsistent Language. International Journal of Approximate Reasoning, 112, 55-84.
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Shulayeva, O., Siddharthan, A., & Wyner, A. (2017). Recognizing cited facts and principles in legal judgements. Artificial Intelligence and Law, 25(1), 107-126.
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Wyner, A. (2016). Working on the argument pipeline: Through flow issues between natural language argument, instantiated arguments, and argumentation frameworks. Argument & Computation, 7(1), 69-89.
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Wyner, A. (2016). A functional perspective on argumentation schemes. Argument & Computation, 7(2-3), 113-133.
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Lin, C., Ibeke, E., Wyner, A., & Guerin, F. (2015). Sentiment-topic modeling in text mining. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(5), 246-254.
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Prakken, H., Wyner, A., Bench-Capon, T., & Atkinson, K. (2015). A formalization of argumentation schemes for legal case-based reasoning in ASPIC+. Journal of Logic and Computation, 25(5), 1141-1166.
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Wyner, A., Bench-Capon, T., Dunne, P., & Cerutti, F. (2015). Senses of ‘argument’ in instantiated argumentation frameworks. Argument & Computation, 6(1), 50-72.
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Wyner, A. & Hoekstra, R. (2012). A legal case OWL ontology with an instantiation of Popov v. Hayashi. Artificial Intelligence and Law, 20(1), 83-107.
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Wyner, A., Bench-Capon, T., & Wyner, A. (2009). Modelling Judicial Context in Argumentation Frameworks. Journal of Logic and Computation, 19(6), 941-968.
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Wyner, A. (2008). An ontology in OWL for legal case-based reasoning. Artificial Intelligence and Law, 16(4), 361-387.
Authored Books
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Wyner, A. (2017). Book chapter: On annotation of the textual contents of Scottish legal instruments IOS Press.
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Wyner, A. & Strass, H. (2017). Advances in Artificial Intelligence: From Theory to Practice Springer Verlag.
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Wyner, A., Nazarenko, A., & Lévy, F. (2016). Controlled Natural Language Springer.
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Wyner, A. (2016). Towards a methodology for formalizing legal texts in LegalRuleML IOS Press.
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Wyner, A. (2015). Passing a USA national bar exam - A first experiment IOS Press.
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Bench-Capon, T., Atkinson, K., & Wyner, A. (2015). Using Argumentation to Structure E-Participation in Policy Making. Springer.
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Wyner, A. (2013). A case study on legal case annotation
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Wyner, A. (2013). Argumentation schemes for reasoning about factors with dimensions
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Athan, T., Boley, H., Governatori, G., Palmirani, M., Paschke, A., & Wyner, A. (2013). Theory, Practice, and Applications of Rules on the Web
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Wyner, A., Bench-Capon, T., & Dunne, P. (2013). Computational Logic in Multi-Agent Systems
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Wyner, A. (2012). A model-based critique tool for policy deliberation
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Wyner, A. (2012). An empirical approach to the semantic representation of laws
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Lloyd-Kelly, M. & Wyner, A. (2012). Advances in User Modeling
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Wyner, A., Riley, L., Hoehndorf, R., & Croset, S. (2012). Information Technology in Bio- and Medical Informatics
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Wyner, A. (2012). Critiquing justifications for action using a semantic model: Demonstration
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Schneider, J., Davis, B., & Wyner, A. (2012). Knowledge Engineering and Knowledge Management
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Wyner, A., Atkinson, K., & Bench-Capon, T. (2012). Electronic Participation
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Wyner, A. (2012). Semi-automated argumentative analysis of online product reviews
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Wyner, A. (2011). On rule extraction from regulations
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Wyner, A. (2011). Populating an online consultation tool
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Wyner, A., Atkinson, K., & Bench-Capon, T. (2011). Electronic Participation
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Wyner, A., Mochales-Palau, R., Moens, M., & Milward, D. (2010). Semantic Processing of Legal Texts
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Wyner, A. (2010). Arguing Global Governance
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Wyner, A., Engers, T., & Bahreini, K. (2010). Electronic Government and the Information Systems Perspective
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Wyner, A. (2010). Lexical semantics and expert legal knowledge towards the identification of legal case factors
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Wyner, A., Angelov, K., Barzdins, G., Damljanovic, D., Davis, B., Fuchs, N., Hoefler, S., Jones, K., Kaljurand, K., Kuhn, T., Luts, M., Pool, J., Rosner, M., Schwitter, R., & Sowa, J. (2010). Controlled Natural Language
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Wyner, A. (2008). Modelling judicial context in argumentation frameworksSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50735
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Wyner, A. (2007). Three senses of "argument"
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Wyner, A. (2007). Towards an extensible argumentation systemSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50737
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Wyner, A. (2006). A functional program for agents, actions, and deontic specificationsSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50738
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Wyner, A. (2006). Deontic Logic and Artificial Normative Systems
Book Chapters
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Liepina, R., Sartor, G., & Wyner, A. (2018). Causal Models of Legal Cases. Lecture Notes in Computer Science (pp. 172-186). Springer International Publishing
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Peters, W. & Wyner, A. (2015). Extracting Hohfeldian relations from text. In Antonino Rotolo (Ed.), Legal Knowledge and Information Systems (pp. 189-190). IOS Press
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Athan, T., Governatori, G., Palmirani, M., Paschke, A., & Wyner, A. (2015). LegalRuleML: Design Principles and Foundations. In Wolfgang Faber, Adrian Paschke. (Ed.), Reasoning Web. Web Logic Rules (pp. 151-188). Springer International Publishing
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Wyner, A., Bench-Capon, T., & Dunne, P. (2009). On the Instantiation of Knowledge Bases in Abstract Argumentation Frameworks. Computational Logic in Multi-Agent Systems -50).
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Wyner, A. (2004). Maintaining Obligations on Stative Expressions in a Deontic Action Logic. Deontic Logic in Computer Science -274).
Conference Contributions
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Anim, k., Robaldo, L., & Wyner, A. (2024). Compliance Checking in the Energy Domain via W3C Standards. In New Frontiers in Artificial Intelligence (pp. 3-18). Springer Nature Switzerland.
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Edwards, J., Wintersberger, P., Clark, L., Rough, D., Doyle, P., Banks, V., Wyner, A., Janssen, C., & Cowan, B. (2021). CUI @ Auto-UI: Exploring the Fortunate and Unfortunate Futures of Conversational Automotive User Interfaces. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 186-189). ACM.
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Bansky, P., Edelstein, E., Pan, J., & Wyner, A. (2020). A Dynamic and Informative Intelligent Survey System Based on Knowledge Graph. In Semantic Technology (pp. 226-241). Springer International Publishing.
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Wyner, A. (2018). A Chatbot Framework for the Children's Legal Centre. In Legal Knowledge and Information Systems (pp. 205-209). IOS Press.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48661
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Fawei, B., Pan, J., Kollingbaum, M., & Wyner, A. (2018). A Methodology for a Criminal Law and Procedure Ontology for Legal Question Answering. In Semantic Technology (pp. 198-214).
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Soares, R., Edelstein, E., Pan, J., & Wyner, A. (2018). Knowledge Driven Intelligent Survey Systems for Linguists. In Semantic Technology-18). Semantic Technology: 8th Joint International Conference, JIST 2018..
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Wyner, A. (2017). On automated defeasible reasoning with controlled natural language and argumentation. In AAAI Publications, Workshops at the Thirty-First AAAI Conference on Artificial IntelligenceSU Repository: https://cronfa.swan.ac.uk/Record/cronfa50682
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Wyner, A. & Peters, W. (2016). Legal text interpretation: Identifying Hohfeldian relations from text. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) (pp. 379-384).SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50684
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Wyner, A. (2016). Passing a USA national bar exam: A first corpus for experimentation. LREC 2016, Tenth International Conference on Language Resources and Evaluation.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50685
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Wyner, A. (2014). Legal interpretations in LegalRuleML.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50694
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Wyner, A. (2014). Mining fine-grained argument elements.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50695
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Wyner, A. (2013). A study on translating regulatory rules from natural language to defeasible logic.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50697
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Bench-Capon, T., Prakken, H., Wyner, A., & Atkinson, K. (2013). Argument schemes for reasoning with legal cases using values. In ICAIL '13 Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law (pp. 13-22). International Conference on Artificial Intelligence and Law.
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Wardeh, M., Wyner, A., Atkinson, K., & Bench-Capon, T. (2013). Argumentation based tools for policy-making. In ICAIL '13 Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law (pp. 249-250). International Conference on Artificial Intelligence and Law.
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Athan, T., Boley, H., Governatori, G., Palmirani, M., Paschke, A., & Wyner, A. (2013). OASIS LegalRuleML. In ICAIL '13 Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law (pp. 3-12). International Conference on Artificial Intelligence and Law.
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Wyner, A. (2012). Arguing from a point of view.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50708
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Wyner, A. (2012). Identifying consumers' arguments in text.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50712
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Atkinson, K., Bench-Capon, T., Cartwright, D., & Wyner, A. (2011). Semantic models for policy deliberation. In ICAIL '11 Proceedings of the 13th International Conference on Artificial Intelligence and Law (pp. 81-90). International Conference on Artificial Intelligence and Law.
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Wyner, A., Bench-Capon, T., & Atkinson, K. (2011). Towards formalising argumentation about legal cases. In ICAIL '11 Proceedings of the 13th International Conference on Artificial Intelligence and Law (pp. 1-10). International Conference on Artificial Intelligence and Law.
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Wyner, A. (2010). Representing deontic concepts for CNLs.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50728
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Wyner, A. (2010). Towards annotating and extracting textual legal case elements.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50729
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Wyner, A. (2010). Web-based mass argumentation in natural language.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50730
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Wyner, A. (2010). What do you mean? Arguing for meaning.SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50731
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Wyner, A., Bench-Capon, T., & Dunne, P. (2009). On the Instantiation of Knowledge Bases in Abstract Argumentation Frameworks. In Computational Logic in Multi-Agent Systems (pp. 34-50).
Supervision
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Computational Semantics of Natural Language for Computational Law (current)
PhDOther supervisor: Dr Julian Hough -
Mind the Gap: Representation and Reasoning for Autonomous Vehicles (current)
PhDOther supervisor: Dr Ulrich Berger -
Automating documentary regulatory compliance in the upstream petroleum sector of Ghana with particular focus on the area of local content and participation. (current)
PhDOther supervisor: Dr Livio Robaldo
Taught Modules
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CS-265 Artificial Intelligence
CS-265 is an introduction to Artificial Intelligence (AI) focusing primarily on reasoning and problem solving as a search for a solution. The central notions of a rational agent and multi-agent systems are used to introduce concepts like beliefs, desires, and intentions that are fundamental to the search for solutions within the context of an observable environment. Further aspects of symbolic AI such as knowledge representation and expert systems, planning, and language processing will be covered. All of these topics are embedded into a human-centred perspective of AI.
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CSC315 Advanced Topics in Artificial Intelligence
This module exposes students to advanced topics in Artificial Intelligence, deepening the range and depth of knowledge of concepts and techniques in AI. Human-centred topics that bear on AI will also be addressed as well as integrations across approaches for Explainable AI. The course may vary topics from year to year from amongst the following or additions as appropriate: advanced machine learning (ML) models and algorithms, ML approaches to NLP, advanced symbolic AI and NLP, integrations of ML and symbolic approaches, and human-centredness (e.g., interpretability, transparency, trust).
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CSC325 Artificial Intelligence
CSC325 is an introduction to Artificial Intelligence (AI) focusing primarily on reasoning and problem solving as a search for a solution. The central notions of a rational agent and multi-agent systems are used to introduce concepts like beliefs, desires, and intentions that are fundamental to the search for solutions within the context of an observable environment. Further aspects of symbolic AI such as knowledge representation and expert systems, planning, and language processing will be covered. All of these topics are embedded into a human-centred perspective of AI.
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CSCM23 Designing-in Trust, Understanding and Negotiation
This module explores state-of-the-art methods and concepts to assist responsible design and development of technology with the aim of creating reliable and trusted systems. The content of this module will be delivered by expert lecturers and practitioners in the areas of trusted computation, bias and explainability in automated decision making and decision support, ethical considerations for AI, argumentation and negotiation, as well as formal methods, such as verification of critical systems.