The Computational Logic and Argumentation Group was formed in 2010 by Professor Francesca Toni with the overarching objective of advancing state-of-the-art models, systems and applications of several incarnations of argumentation as broadly understood in AI. The targeted areas for this research group are therefore wide-ranging. From a theoretical standpoint, the group defines a plethora of frameworks for computational argumentation, studies the semantic and algorithmic foundations of these frameworks as well as using them to provide the argumentative underpinnings of a host of logic-based paradigms in knowledge representation and reasoning, e.g. classical logic, (abductive) logic programming and non-monotonic reasoning. Meanwhile, the group develops and deploys state-of-the-art systems for computational argumentation in combination with methodologies for mining argumentation frameworks from data, and text in natural language processing in particular. The applications of these systems and methodologies are diverse and far-reaching, given argumentation’s inherent suitability to various contexts where conflict resolution and dialectical reasoning are appropriate. Applications include fake news detection and review aggregation, where the automated extraction and analysis of argumentation frameworks from textual data is beneficial, and healthcare and legal applications, where argumentation-based, interactive explanations have the capability to anthropomorphise machines as they explain outputs to humans.
For more information, see the Computational Logic and Argumentation Group's standalone website from the Department of Computing.