4 papers
On Generating Monolithic and Model Reconciling Explanations in Probabilistic Scenarios
Stylianos Loukas Vasileiou, William Yeoh, Alessandro Previti +1
Explanation generation frameworks aim to make AI systems' decisions transparent and understandable to human users. However, generating explanations in uncertain environments charac…
TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling
Stylianos Loukas Vasileiou, William Yeoh
We present TRACE-CS, a novel hybrid system that combines symbolic reasoning with large language models (LLMs)to address contrastive queries in course scheduling problems. TRACE-CS…
A Methodology for Incompleteness-Tolerant and Modular Gradual Semantics for Argumentative Statement Graphs
Antonio Rago, Stylianos Loukas Vasileiou, Francesca Toni +2
Gradual semantics (GS) have demonstrated great potential in argumentation, in particular for deploying quantitative bipolar argumentation frameworks (QBAFs) in a number of real-wor…
Inferring Implicit Goals Across Differing Task Models
Silvia Tulli, Stylianos Loukas Vasileiou, Mohamed Chetouani +1
One of the significant challenges to generating value-aligned behavior is to not only account for the specified user objectives but also any implicit or unspecified user requiremen…