Dr Simon Wells
| Biography | I study how people know, reason, and communicate with respect to their beliefs, knowledge, and ideas, and how these can be used to improve both machine reasoning and human-machine interaction. Argumentation Theory is the unifying concept, bringing together aspects of knowledge representation, reasoning, and communication into a cohesive approach to Artificial Intelligence. In this approach, arguments are complexes formed from premises, inferences, and conclusions. These provide a foundation for an agent to record information about its world in the form of knowledge. This knowledge is subsequently used to reason, defeasibly and non-monotonically, using techniques from computational argumentation. Finally, moving from monological argument towards argumentative dialogue, provides a basis both for communicating decisions made to other agents, both machine and human, but also for criticising, persuading, deliberating and other interactions that enable robust joint decision making and subsequent action. I see the cohesiveness of argumentation based knowledge, reasoning, and communication processes as a foundation for addressing a range of AI and Computer Science research questions across a diversity of applied problem domains. I began my career at the University of Dundee where I researched a thesis on inter-agent communication using argumentative dialogue whilst employed on the EPSRC-funded Information Exchange Project. After my doctoral research I stayed in the School of Computing at Dundee until 2011. During this time I lectured across the undergraduate Computer Science curriculum whilst helping establish the nascent Argumentation Research Group. In 2011, I joined the Open Microscopy Environment (OME) project and worked on joint research between OME and the Ninewells Hospital Health Informatics Centre. In 2012 I joined the School of Computing at the University of Aberdeen where I was on employed on a large EU-funded IP project called SUPERHUB. On SUPERHUB I researched the roles of persuasive technology and behaviour change mechanisms in sustainable transport systems. In 2014 I joined the school of computing at Edinburgh Napier as a lecturer. Since joining Napier I have taught across the entire undergraduate curriculum, including large-scale service teaching in programming fundamentals, algorithms & data structures,mobile application development, and web technologies, and more targetted, research led teaching in advertised web technologies and multiagent systems. During this period I have further developed my interest in inter- and trans-disciplinary topics, contributing to both the funded REMAR and WOSHH projects with the School of Life Sciences. |
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| Research Interests | My interests are broadly in argumentation theory and computational argument with specific interests in dialogues models, strategic interaction, and deceptive communication, and applications to human behaviour change and effective and efficient communication amongst heterogeneous groups of people and agents. My recent research has covered a variety of topics, nearly all of which are tied to the my core interests in Argumentation and Dialogue. In recent years I have researched and published, often collaboratively, on a range of argumentation and AI oriented topics. These topics will form the basis for the directions in which my research programme develops in the short to medium term and include: • Trust between people and intelligent machines (Andras et al, 2019) • Persuasive technology and human-machine interaction in the sustainable transport domain (Wells & Pangbourne, 2016, Pangbourne et al, 2017, Gabrielli et al, 2014) • Deceptive communication between people and intelligent machines (Wells & Baker, 2019, Wells & Baker, 2018, Baker & Wells, 2017) • Refining computational models of dialogue, i.e. how and when people licitly or illicitly repeat statements (Wells & Snaith, 2022), and how burdens of proof apply to proposals during deliberative processes (Godden & Wells, 2022) • Techniques for visualisation of large scale argumentative datasets (Khartabil et al, 2021) • Open infrastructures for argumentative technologies (Wells, 2020) • Argumentative Strength (Zenker et al, 2019, Zenker et al, 2023 (under review)) • Dialogue Strategy (Wells, 2016) |
| Scopus Author ID | 8905957400 |