7 papers
OmouAI: Argumentative Human-AI Policy Deliberation with Simulated Personas
Stylianos Loukas Vasileiou, Antonio Rago, William Yeoh +1
Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions include humans and take place in…
Discourse-Aware Policy Analysis with Argumentation: A Hybrid LLM-Symbolic Framework for Disaster Governance
Stylianos Loukas Vasileiou, Olga Derendiaeva
Policy documents shape governance outcomes, but their reasoning is often implicit. Participatory commitments and managerial control routinely coexist in the same text, and the tens…
Argumentative Human-AI Decision-Making: Toward AI Agents That Reason With Us, Not For Us
Stylianos Loukas Vasileiou, Antonio Rago, Francesca Toni +1
Computational argumentation offers formal frameworks for transparent, verifiable reasoning but has traditionally been limited by its reliance on domain-specific information and ext…
How Do People Revise Inconsistent Beliefs? Examining Belief Revision in Humans with User Studies
Stylianos Loukas Vasileiou, Antonio Rago, Maria Vanina Martinez +1
Understanding how humans revise their beliefs in light of new information is crucial for developing AI systems which can effectively model, and thus align with, human reasoning. Wh…
Does Your AI Agent Get You? A Personalizable Framework for Approximating Human Models from Argumentation-based Dialogue Traces
Yinxu Tang, Stylianos Loukas Vasileiou, William Yeoh
Explainable AI is increasingly employing argumentation methods to facilitate interactive explanations between AI agents and human users. While existing approaches typically rely on…
Explainable Distributed Constraint Optimization Problems
Ben Rachmut, Stylianos Loukas Vasileiou, Nimrod Meir Weinstein +2
The Distributed Constraint Optimization Problem (DCOP) formulation is a powerful tool to model cooperative multi-agent problems that need to be solved distributively. A core assump…
Approximating Human Models During Argumentation-based Dialogues
Yinxu Tang, Stylianos Loukas Vasileiou, William Yeoh
Explainable AI Planning (XAIP) aims to develop AI agents that can effectively explain their decisions and actions to human users, fostering trust and facilitating human-AI collabor…