Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile. - Lucas Rizzo; Pierpaolo Dondio; Sarah Jane Delany; Luca Longo (AIAI, 2016)

Representing and Inferring Mental Workload via Defeasible Reasoning: A Comparison with the NASA Task Load Index and the Workload Profile. - Lucas Rizzo; Luca Longo (AI³@AI*IA, 2017)

On Demonstrating the Impact of Defeasible Reasoning in Practice via a Multi-layer Argument-based Framework. - Lucas Rizzo (AAMAS, 2017)

A Qualitative Investigation of the Explainability of Defeasible Argumentation and Non-Monotonic Fuzzy Reasoning. - Lucas Rizzo; Luca Longo (AICS, 2018)

Inferential Models of Mental Workload with Defeasible Argumentation and Non-monotonic Fuzzy Reasoning: a Comparative Study. - Lucas Rizzo; Luca Longo (AI³@AI*IA, 2018)

A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers. - Lucas Rizzo; Ljiljana Majnaric; Luca Longo (AI*IA, 2018)

An Investigation of Argumentation Theory for the Prediction of Survival in Elderly Using Biomarkers. - Lucas Rizzo; Ljiljana Majnaric; Pierpaolo Dondio; Luca Longo (AIAI, 2018)

LightGWAS: A Novel Machine Learning Procedure for Genome-Wide Association Study. - Bruno Ambrozio; Luca Longo; Lucas Rizzo (AICS, 2020)

Exploring the potential of defeasible argumentation for quantitative inferences in real-world contexts: An assessment of computational trust. - Lucas Rizzo; Pierpaolo Dondio; Luca Longo (AICS, 2020)

A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence. - Giulia Vilone; Lucas Rizzo; Luca Longo (AICS, 2020)

An empirical evaluation of the inferential capacity of defeasible argumentation, non-monotonic fuzzy reasoning and expert systems. - Lucas Rizzo; Luca Longo (Expert Syst. Appl., 2020)

Examining the modelling capabilities of defeasible argumentation and non-monotonic fuzzy reasoning. - Luca Longo; Lucas Rizzo; Pierpaolo Dondio (Knowl. Based Syst., 2021)

A Novel Structured Argumentation Framework for Improved Explainability of Classification Tasks. - Lucas Rizzo (xAI (3), 2023)

A novel structured argumentation framework for improved explainability of classification tasks. - Lucas Rizzo; Luca Longo (CoRR, 2023)

Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts. - Lucas Rizzo; Luca Longo (Inf. Fusion, 2023)

ArgFrame: A multi-layer, web, argument-based framework for quantitative reasoning. - Lucas Rizzo (Softw. Impacts, 2023)

A Novel Integration of Data-Driven Rule Generation and Computational Argumentation for Enhanced Explainable AI. - Lucas Rizzo; Damiano Verda; Serena Berretta; Luca Longo (Mach. Learn. Knowl. Extr., 2024)