activity
20122023
most citedDistributed Constraint Optimization Problems and Applications: A Survey

207 citations · 322 across the 14 of their papers we have counts for

collaborators

15 papers

cs.AI2023

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…

cs.AI2023

Using Simple Incentives to Improve Two-Sided Fairness in Ridesharing Systems

Ashwin Kumar, Yevgeniy Vorobeychik, William Yeoh

State-of-the-art order dispatching algorithms for ridesharing batch passenger requests and allocate them to a fleet of vehicles in a centralized manner, optimizing over the estimat…

cs.CR2022★ 1 cited

Blockchain-based Digital Twin for Supply Chain Management: State-of-the-Art Review and Future Research Directions

Jiongbin Liu, William Yeoh, Youyang Qu +1

Supply chain management (SCM) plays a vital role in the global economy, as evidenced by recent COVID-19 supply chain challenges. Traditional SCM faces security and efficiency issue…

cs.AI2020★ 3 cited

On the Relationship Between KR Approaches for Explainable Planning

Stylianos Loukas Vasileiou, William Yeoh, Tran Cao Son

In this paper, we build upon notions from knowledge representation and reasoning (KR) to expand a preliminary logic-based framework that characterizes the model reconciliation prob…

cs.AI2020★ 1 cited

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…

cs.MA2020

A Particle Swarm Inspired Approach for Continuous Distributed Constraint Optimization Problems

Moumita Choudhury, Amit Sarker, Md. Mosaddek Khan +1

Distributed Constraint Optimization Problems (DCOPs) are a widely studied framework for coordinating interactions in cooperative multi-agent systems. In classical DCOPs, variables…