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Reconciling “Data for Learning” with “Data for Arguing”

Career / Placement Opportunities / BSc/MSc Topics / Reconciling “Data for Learning” with “Data for Arguing”
17 January. 2021
The data-driven view of Artificial Intelligence that is currently at the focus of research and industrial attention can be thought to treat a dataset through a collaborative prism, as a collection whose members have certain commonalities; one wishes to identify these commonalities by embracing the statistics of the collection over the views supported by any single member. Case-based reasoning, on the other hand, treats a dataset through a combative prism, as a loose grouping of individuals that support divergent views; one wishes to resolve the tension between these divergent views by identifying which individual makes a stronger case over the other members of the collection. The project seeks to reconcile these two views of data, by bringing together techniques from machine learning and formal argumentation. Depending on the internship type, the project can be adapted towards the development and analysis of a formal framework for this reconciliation, or towards the design and empirical evaluation of simple heuristics that acknowledge both the statistical and argumentative nature of data.