| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 10 | Longo L., Berretta S., Verda D., Rizzo L. | Computational argumentation and automatic rule-generation for explainable data-driven modeling | IEEE Access | 2025 |   
@ARTICLE{Longo2025IEEEAccess, author={Longo, Luca and Berretta, Serena and Verda, Damiano and Rizzo, Lucas}, journal={IEEE Access}, title={Computational argumentation and automatic rule-generation for explainable data-driven modeling}, year={2025}, volume={}, number={}, pages={1-1}, doi={10.1109/ACCESS.2025.3618992}} [Close]
| Rule-base systems • Explainable Artificial Intelligence • Logic Learning Machine • Non-monotonic reasoning • Defeasible Reasoning • Explainability • Computational argumentation • Argumentation semantics • Explainability |
| 9 | Vilone G., Longo L. | An Examination of the Effect of the Inconsistency Budget in Weighted Argumentation Frameworks and their Impact on the Interpretation of Deep Neural Networks | Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) | 2023 | 
@inproceedings{DBLP:conf/xai/ViloneL23a, author = {Giulia Vilone and Luca Longo}, editor = {Luca Longo}, title = {An Examination of the Effect of the Inconsistency Budget in Weighted Argumentation Frameworks and their Impact on the Interpretation of Deep Neural Networks}, booktitle = {Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lisbon, Portugal, July 26-28, 2023}, series = {{CEUR} Workshop Proceedings}, volume = {3554}, pages = {53--58}, publisher = {CEUR-WS.org}, year = {2023}, url = {https://ceur-ws.org/Vol-3554/paper10.pdf} } [Close]
| Explainable artificial intelligence • Argumentation • Non-monotonic reasoning • Automatic attack extraction • Weighted argumentation frameworks • Inconsistency budget • Machine Learning • Neural Networks |
| 8 | Rizzo L., Longo L. | Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts | Information fusion | 2023 |
@article{RIZZOLongo2022, title = {Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts}, journal = {Information Fusion}, volume = {89}, pages = {537-566}, year = {2023}, issn = {1566-2535}, doi = {https://doi.org/10.1016/j.inffus.2022.08.025}, url = {https://www.sciencedirect.com/science/article/pii/S1566253522001245}, author = {Lucas Rizzo and Luca Longo}, keywords = {Defeasible argumentation, Knowledge-based systems, Non-monotonic reasoning, Argumentation theory, Fuzzy logic, Expert systems, Computational trust} } [Close]
| Defeasible Argumentation • Knowledge-based Systems • Non-monotonic Reasoning • Fuzzy Logic • Expert Systems • Computational Trust |
| 7 | Vilone G. Longo L. | A global model-agnostic XAI method for the automatic formation of an abstract argumentation framework and its objective evaluation. | 1st Int. Workshop on Argumentation for eXplainable AI (with 9th Int. Conference on Computational Models of Argument, COMMA 2022) | 2022 |
@inproceedings{ViloneLongo2022XAIArg, author = {Giulia Vilone and Luca Longo}, title = {A global model-agnostic XAI method for the automatic formation of an abstract argumentation framework and its objective evaluation.}, booktitle = {1st International Workshop on Argumentation for eXplainable AI co-located with 9th International Conference on Computational Models of Argument (COMMA 2022)}, series = {{CEUR} Workshop Proceedings}, volume = {3209}, publisher = {CEUR-WS.org}, year = {2022}, url = {http://ceur-ws.org/Vol-3209/2119.pdf} } [Close]
| Explainable artificial intelligence • Argumentation • Non-monotonic reasoning • Method evaluation • Metrics
of explainability |
| 6 | Rizzo L. Dondio P., Longo L. | Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust | Proceedings for the 28th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, December 7-8, 2020 | 2020 |
@inproceedings{DBLP:conf/aics/RizzoDL20, author = {Lucas Rizzo and Pierpaolo Dondio and Luca Longo}, editor = {Luca Longo and Lucas Rizzo and Elizabeth Hunter and Arjun Pakrashi}, title = {Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust}, booktitle = {Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Republic of Ireland, December 7-8, 2020}, series = {{CEUR} Workshop Proceedings}, volume = {2771}, pages = {37--48}, publisher = {CEUR-WS.org}, year = {2020}, url = {http://ceur-ws.org/Vol-2771/AICS2020\_paper\_13.pdf} } [Close]
| Defeasible Argumentation • Argumentation Theory • Explainable
Artificial Intelligence • Non-monotonic Reasoning • Computational Trust |
| 5 | Rizzo L., Longo L. | Inferential models of mental workload with defeasible argumentation and non-monotonic fuzzy reasoning: a comparative study | 2nd Workshop on Advances In Argumentation In Artificial Intelligence, co-located with XVII International Conference of the Italian Association for Artificial Intelligence | 2019 |
@inproceedings{RizzoL18Inferential, author = {Lucas Rizzo and Luca Longo}, title = {Inferential Models of Mental Workload with Defeasible Argumentation and Non-monotonic Fuzzy Reasoning: a Comparative Study}, booktitle = {Proceedings of the 2nd Workshop on Advances In Argumentation In Artificial Intelligence, co-located with {XVII} International Conference of the Italian Association for Artificial Intelligence, AI{\({^3}\)}@AI*IA 2018, 20-23 November 2018, Trento, Italy}, pages = {11--26}, year = {2018} } [Close]
| Argumentation Theory • Non-monotonic Reasoning • Fuzzy Logic • Mental workload • Defeasible Reasoning • Modeling • Artificial Intelligence |
| 4 | Rizzo L., Longo L. | A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning | 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science | 2018 |
@inproceedings{RizzoL18Explainability, author = {Lucas Rizzo and Luca Longo}, title = {A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning}, booktitle = {Proceedings for the 26th {AIAI} Irish Conference on Artificial Intelligence and Cognitive Science Trinity College Dublin, Dublin, Ireland, December 6-7th, 2018.}, pages = {138--149}, year = {2018} } [Close]
| Defeasible Argumentation • Non-monotonic Reasoning • Fuzzy Reasoning • Argumentation Theory • Explainable Artificial Intelligence • Artificial Intelligence • Modeling |
| 3 | Rizzo L., Majnaric L., Longo L. | A comparative study of defeasible argumentation and non-monotonic fuzzy reasoning for elderly survival prediction using biomarkers | International Conference of the Italian Association for Artificial Intelligence | 2018 |
@inproceedings{rizzo2018comparative, title={A comparative study of defeasible argumentation and non-monotonic fuzzy reasoning for elderly survival prediction using biomarkers}, author={Rizzo, Lucas and Majnaric, Ljiljana and Longo, Luca}, booktitle={International Conference of the Italian Association for Artificial Intelligence}, pages={197--209}, year={2018}, organization={Springer} } [Close]
| Argumentation Theory • Non-monotonic Reasoning • Defeasible Reasoning • Fuzzy Reasoning • Possibility Theory • Biomarkers • Modeling • Artificial Intelligence |
| 2 | Longo L. | Formalising human mental workload as non-monotonic concept for adaptive and personalised web-design | International Conference on User Modeling, Adaptation, and Personalization | 2012 |
@inproceedings{longo2012formalising, title={Formalising human mental workload as non-monotonic concept for adaptive and personalised web-design}, author={Longo, Luca}, booktitle={International Conference on User Modeling, Adaptation, and Personalization}, pages={369--373}, year={2012}, organization={Springer} } [Close]
| Human Mental Workload • Non-monotonic Reasoning • Argumentation Theory • Human-Computer Interaction • Web Design |
| 1 | Longo L., Dondio P., Riccardo B., Butterfield A., Barrett S. | Enabling Adaptation in Trust Computations | Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns | 2009 |
@inproceedings{luca2009enabling, title={Enabling adaptation in trust computations}, author={Luca, Longo and Pierpaolo, Dondio and Riccardo, Bresciani and Stephen, Barrett and Andrew, Butterfield}, booktitle={Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD'09. Computation World}, pages={701--706}, year={2009}, organization={IEEE} } [Close]
| Computational Trust • Adaptation • Multi-agent Systems • Web 2.0 • Non-monotonic Reasoning • Modeling |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |