14 citations · 80 across the 19 of their papers we have counts for
21 papers
Dialectical Reconciliation via Structured Argumentative Dialogues
Stylianos Loukas Vasileiou, Ashwin Kumar, William Yeoh +2
We present a novel framework designed to extend model reconciliation approaches, commonly used in human-aware planning, for enhanced human-AI interaction. By adopting a structured…
ASPER: Answer Set Programming Enhanced Neural Network Models for Joint Entity-Relation Extraction
Trung Hoang Le, Huiping Cao, Tran Cao Son
A plethora of approaches have been proposed for joint entity-relation (ER) extraction. Most of these methods largely depend on a large amount of manually annotated training data. H…
On Model Reconciliation: How to Reconcile When Robot Does not Know Human's Model?
Ho Tuan Dung, Tran Cao Son
The Model Reconciliation Problem (MRP) was introduced to address issues in explainable AI planning. A solution to a MRP is an explanation for the differences between the models of…
Answer Set Planning: A Survey
Tran Cao Son, Enrico Pontelli, Marcello Balduccini +1
Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, i.e., solutions to planning problems, that transform a given state of the world to another s…
exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules
Ly Ly Trieu, Tran Cao Son, Marcello Balduccini
We present an enhancement of exp(ASP), a system that generates explanation graphs for a literal l - an atom a or its default negation ~a - given an answer set A of a normal logic p…
DMAPF: A Decentralized and Distributed Solver for Multi-Agent Path Finding Problem with Obstacles
Poom Pianpak, Tran Cao Son
Multi-Agent Path Finding (MAPF) is a problem of finding a sequence of movements for agents to reach their assigned location without collision. Centralized algorithms usually give o…