33 citations · 56 across the 26 of their papers we have counts for
27 papers
An Approach to the Abstract Interpretation of Goal-Directed Answer Set Programming
Daniel Jurjo-Rivas, Joaquín Arias, Gopal Gupta +3
Abstract Interpretation infers and verifies program properties by over-approximating program semantics. It has been highly successful for (Constraint) Logic Programming, enabling t…
Event Calculus Meets Hybrid ASP
Ondřej Vašíček, Joaquín Arias, Jan Fiedor +5
Event Calculus (EC) implemented in answer set programming (ASP) has proven suitable for specifying requirements on safety-critical systems thanks to its elegant representation of b…
On Zeno-like Behaviors in the Event Calculus with Goal-directed Answer Set Programming
Ondřej Vašíček, Joaquin Arias, Jan Fiedor +5
It has been argued that Event Calculus (EC) is suitable for modeling high-level specifications of safety-critical cyber-physical systems. The primary advantage lies in the rather s…
P2C: Path to Counterfactuals
Sopam Dasgupta, Sadaf MD Halim, Joaquín 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, Joaquín 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,…
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…
VECSR: Virtually Embodied Common Sense Reasoning System
Alexis R. Tudor, Joaquín Arias, Gopal Gupta
The development of autonomous agents has seen a revival of enthusiasm due to the emergence of LLMs, such as GPT-4o. Deploying these agents in environments where they coexist with h…
CoGS: Model Agnostic Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, Joaquín 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…
Automating Semantic Analysis of System Assurance Cases using Goal-directed ASP
Anitha Murugesan, Isaac Wong, Joaquín Arias +6
Assurance cases offer a structured way to present arguments and evidence for certification of systems where safety and security are critical. However, creating and evaluating these…
Early Validation of High-level System Requirements with Event Calculus and Answer Set Programming
Ondřej Vašíček, Joaquin Arias, Jan Fiedor +6
This paper proposes a new methodology for early validation of high-level requirements on cyber-physical systems with the aim of improving their quality and, thus, lowering chances…
A Reliable Common-Sense Reasoning Socialbot Built Using LLMs and Goal-Directed ASP
Yankai Zeng, Abhiramon Rajashekharan, Kinjal Basu +3
The development of large language models (LLMs), such as GPT, has enabled the construction of several socialbots, like ChatGPT, that are receiving a lot of attention for their abil…
CoGS: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, Joaquín 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…
CFGs: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, Joaquín Arias, Elmer Salazar +1
Machine learning models that automate decision-making are increasingly used in consequential areas such as loan approvals, pretrial bail approval, and hiring. Unfortunately, most o…
Counterfactual Generation with Answer Set Programming
Sopam Dasgupta, Farhad Shakerin, Joaquín Arias +2
Machine learning models that automate decision-making are increasingly being used in consequential areas such as loan approvals, pretrial bail approval, hiring, and many more. Unfo…
Counterfactual Explanation Generation with s(CASP)
Sopam Dasgupta, Farhad Shakerin, Joaquín Arias +2
Machine learning models that automate decision-making are increasingly being used in consequential areas such as loan approvals, pretrial bail, hiring, and many more. Unfortunately…
Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs
Yankai Zeng, Abhiramon Rajasekharan, Parth Padalkar +3
Achieving human-like communication with machines remains a classic, challenging topic in the field of Knowledge Representation and Reasoning and Natural Language Processing. These…
Building Information Modeling Using Constraint Logic Programming
Joaquín Arias, Seppo Törmä, Manuel Carro +1
Building Information Modeling (BIM) produces three-dimensional models of buildings combining the geometrical information with a wide range of properties. BIM is slowly but inevitab…
Towards Dynamic Consistency Checking in Goal-directed Predicate Answer Set Programming
Joaquín Arias, Manuel Carro, Gopal Gupta
Goal-directed evaluation of Answer Set Programs is gaining traction thanks to its amenability to create AI systems that can, due to the evaluation mechanism used, generate explanat…
Knowledge-Assisted Reasoning of Model-Augmented System Requirements with Event Calculus and Goal-Directed Answer Set Programming
Brendan Hall, Sarat Chandra Varanasi, Jan Fiedor +7
We consider requirements for cyber-physical systems represented in constrained natural language. We present novel automated techniques for aiding in the development of these requir…
Modeling and Reasoning in Event Calculus using Goal-Directed Constraint Answer Set Programming
Joaquín Arias, Manuel Carro, Zhuo Chen +1
Automated commonsense reasoning is essential for building human-like AI systems featuring, for example, explainable AI. Event Calculus (EC) is a family of formalisms that model com…
Knowledge-driven Natural Language Understanding of English Text and its Applications
Kinjal Basu, Sarat Varanasi, Farhad Shakerin +2
Understanding the meaning of a text is a fundamental challenge of natural language understanding (NLU) research. An ideal NLU system should process a language in a way that is not…
A Theoretical Study of (Full) Tabled Constraint Logic Programming
Joaquín Arias, Manuel Carro
Logic programming with tabling and constraints (TCLP, tabled constraint logic programming) has been shown to be more expressive and, in some cases, more efficient than LP, CLP, or…
Justifications for Goal-Directed Constraint Answer Set Programming
Joaquín Arias, Manuel Carro, Zhuo Chen +1
Ethical and legal concerns make it necessary for programs that may directly influence the life of people (via, e.g., legal or health counseling) to justify in human-understandable…