Argumentation Technology for Explainable Artificial Intelligence


This PhD thesis will be developed in the context of the eXplica-IA project of excellence (funded by the "Consellería de Educación, Universidade e Formación Profesional of the Xunta de Galicia" through accreditation ED431F 2018/02), under supervision of Jose M. Alonso. The main objective of this project is to answer the scientific challenge of designing and developing a new generation of algorithms and Artificial Intelligence (AI) techniques which can provide self-explanatory capabilities to Intelligent Systems; that is, with the capacities to explain their behavior and decisions in Natural Language clearly and without linguistic ambiguities, both to expert and non-expert users. More precisely, this PhD thesis is aimed at defining, designing, developing and validating conversational agents endowed with credibility through argument mining and generation capabilities in the context of Explainable AI. Main challenges to face are: modelling context and common ground; dealing with reference expressions; handling implicit knowledge; etc.


We are looking for an outstanding and highly motivated candidate, with initiative, creativity and team-working ability, including working in interdisciplinary research groups. Candidates should fulfil the following eligibility criteria:

  • A Degree in Computer Sciences, Telecommunication Engineering, Data Science, Artificial Intelligence or in another related area within the European Higher Education System.
  • It is recommendable that the candidate already has (or is enrolled in) a Master degree or an equivalent University Degree (minimum 300 ECTS) that allows to start a PhD Program at the University of Santiago de Compostela.
  • Excellent academic record, minimum of 8.5, will be required to be able to request a predoctoral contract from regional or national Government. A financial line is offered during the time in which the student is not ready to apply for the predoctoral contract (maximum one year, economic conditions depending on the profile of the candidate).
  • Good computational skills.
  • Very good English level.
  • It is desirable basic knowledge on Artificial Intelligence and Argumentation, but also on Natural Language Processing and Generation.


  • F. Macagno, D. Walton, C. Reed, “Argumentation schemes. History, classifications, and computational applications, Journal of Applied Logics, 4(8):2493-2556, 2017.
  • C. Sierra, R. López de Mántaras, S. J. Simoff, “The argumentative mediator”, EUMAS/AT, pp. 439-454, 2016.
  • I. Zukerman, R. McConachy, S. George, “Using argumentation strategies in automated argument generation”, Proceedings of the First International Conference on Natural Language Generation (INLG), pp. 55-62, 2000.

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