Lucas Rizzo

Orcid: 0000-0001-9805-5306

According to our database1, Lucas Rizzo authored at least 16 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Links

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Bibliography

2023
ArgFrame: A multi-layer, web, argument-based framework for quantitative reasoning.
Softw. Impacts, September, 2023

Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts.
Inf. Fusion, 2023

A novel structured argumentation framework for improved explainability of classification tasks.
CoRR, 2023

A Novel Structured Argumentation Framework for Improved Explainability of Classification Tasks.
Proceedings of the Explainable Artificial Intelligence, 2023

2021
Examining the modelling capabilities of defeasible argumentation and non-monotonic fuzzy reasoning.
Knowl. Based Syst., 2021

2020
An empirical evaluation of the inferential capacity of defeasible argumentation, non-monotonic fuzzy reasoning and expert systems.
Expert Syst. Appl., 2020

A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence.
Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, 2020

Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust.
Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, 2020

LightGWAS: A Novel Machine Learning Procedure for Genome-Wide Association Study.
Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, 2020

2018
An Investigation of Argumentation Theory for the Prediction of Survival in Elderly Using Biomarkers.
Proceedings of the Artificial Intelligence Applications and Innovations, 2018

A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers.
Proceedings of the AI*IA 2018 - Advances in Artificial Intelligence, 2018

Inferential Models of Mental Workload with Defeasible Argumentation and Non-monotonic Fuzzy Reasoning: a Comparative Study.
Proceedings of the 2nd Workshop on Advances In Argumentation In Artificial Intelligence, 2018

A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning.
Proceedings of the Proceedings for the 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science Trinity College Dublin, 2018

2017
On Demonstrating the Impact of Defeasible Reasoning in Practice via a Multi-layer Argument-based Framework.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Representing and Inferring Mental Workload via Defeasible Reasoning: A Comparison with the NASA Task Load Index and the Workload Profile.
Proceedings of the 1st Workshop on Advances In Argumentation In Artificial Intelligence co-located with XVI International Conference of the Italian Association for Artificial Intelligence, 2017

2016
Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile.
Proceedings of the Artificial Intelligence Applications and Innovations, 2016


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