7 papers · 1 filter
Modeling Deontic Modal Logic in ASP
Gopal Gupta, Abhiramon Rajasekharan, Alexis R. Tudor +2
We consider the problem of implementing deontic modal logic. We show how (deontic) modal operators can be elegantly and directly expressed using default negation (negation-as-failu…
Building Trustworthy AI by Addressing its 16+2 Desiderata with Goal-Directed Commonsense Reasoning
Alexis R. Tudor, Yankai Zeng, Huaduo Wang +2
Current advances in AI and its applicability have highlighted the need to ensure its trustworthiness for legal, ethical, and even commercial reasons. Sub-symbolic machine learning…
P2C: Path to Counterfactuals
Sopam Dasgupta, Sadaf MD Halim, JoaquÃn Arias +2
Machine-learning models are increasingly driving decisions in high-stakes settings, such as finance, law, and hiring, thus, highlighting the need for transparency. However, the key…
MC3G: Model Agnostic Causally Constrained Counterfactual Generation
Sopam Dasgupta, Sadaf MD Halim, JoaquÃn Arias +2
Machine learning models increasingly influence decisions in high-stakes settings such as finance, law and hiring, driving the need for transparent, interpretable outcomes. However,…
CoGS: Model Agnostic Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, JoaquÃn Arias, Elmer Salazar +1
Machine learning models are increasingly used in critical areas such as loan approvals and hiring, yet they often function as black boxes, obscuring their decision-making processes…
CoGS: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, JoaquÃn Arias, Elmer Salazar +1
Machine learning models are increasingly used in areas such as loan approvals and hiring, yet they often function as black boxes, obscuring their decision-making processes. Transpa…