4 citations · 4 across the 8 of their papers we have counts for
8 papers
A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)
Michael Thielscher, Tran Cao Son
We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent gains the belief in some state…
xDNN(ASP): Explanation Generation System for Deep Neural Networks powered by Answer Set Programming
Ly Ly Trieu, Tran Cao Son
Explainable artificial intelligence (xAI) has gained significant attention in recent years. Among other things, explainablility for deep neural networks has been a topic of intensi…
SLogic: Subgraph-Informed Logical Rule Learning for Knowledge Graph Completion
Trung Hoang Le, Tran Cao Son, Ishtiaq Ahmed +1
Logical rule-based methods offer an interpretable approach to knowledge graph completion (KGC) by capturing compositional relationships in the form of human-readable inference rule…
An LLM + ASP Workflow for Joint Entity-Relation Extraction
Trang Tran, Trung Hoang Le, Huiping Cao +1
Joint entity-relation extraction (JERE) identifies both entities and their relationships simultaneously. Traditional machine-learning based approaches to performing this task requi…
Routing and Scheduling in Answer Set Programming applied to Multi-Agent Path Finding: Preliminary Report
Roland Kaminski, Torsten Schaub, Tran Cao Son +2
We present alternative approaches to routing and scheduling in Answer Set Programming (ASP), and explore them in the context of Multi-agent Path Finding. The idea is to capture the…
Taking Cognition Seriously: A generalised physics of cognition
Sophie Alyx Taylor, Son Cao Tran, Dan V. Nicolau
The study of complex systems through the lens of category theory consistently proves to be a powerful approach. We propose that cognition deserves the same category-theoretic treat…
Generating explanations for answer set programming applications
Ly Ly Trieu, Tran Cao Son, Enrico Pontelli +1
We present an explanation system for applications that leverage Answer Set Programming (ASP). Given a program P, an answer set A of P, and an atom a in the program P, our system ge…
A State-Based Regression Formulation for Domains with Sensing Actions<br> and Incomplete Information
Le-Chi Tuan, Chitta Baral, Tran Cao Son
We present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and emp…