1 citations · 1 across the 2 of their papers we have counts for
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…
On Exploiting Hitting Sets for Model Reconciliation
Stylianos Loukas Vasileiou, Alessandro Previti, William Yeoh
In human-aware planning, a planning agent may need to provide an explanation to a human user on why its plan is optimal. A popular approach to do this is called model reconciliatio…
Machine Reasoning Explainability
Kristijonas Cyras, Ramamurthy Badrinath, Swarup Kumar Mohalik +5
As a field of AI, Machine Reasoning (MR) uses largely symbolic means to formalize and emulate abstract reasoning. Studies in early MR have notably started inquiries into Explainabl…
Cautious reasoning in ASP via minimal models and unsatisfiable cores
Mario Alviano, Carmine Dodaro, Matti Järvisalo +2
Answer Set Programming (ASP) is a logic-based knowledge representation framework, supporting---among other reasoning modes---the central task of query answering. In the proposition…