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Trustworthy AI - Integrating Learning, Optimization and Reasoning

First International Workshop, TAILOR 2020, Virtual Event, September 4–5, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Fredrik Heintz

    1. Department of Computer and Information Science, Linköping University, Linköping, Sweden

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  2. Michela Milano

    1. ALMA-AI Research Institute on Human-Centered AI, University of Bologna, Bologna, Italy

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    You can also search for this editor in PubMed   Google Scholar

  3. Barry O'Sullivan

    1. Department of Computer Science, University College Cork, Cork, Ireland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12641)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: TAILOR 2020.

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Table of contents (23 papers)

  1. Front Matter

    Pages i-xi
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  2. Trustworthy AI

    1. Front Matter

      Pages 1-1
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    2. Towards Automated GDPR Compliance Checking

      • Tomer Libal
      Pages 3-19

    3. Underestimation Bias and Underfitting in Machine Learning

      • Pádraig Cunningham, Sarah Jane Delany
      Pages 20-31

    4. Consensus for Collaborative Creation of Risk Maps for COVID-19

      • M. Rebollo, C. Carrascosa, A. Palomares
      Pages 32-48

    5. Guided-LORE: Improving LORE with a Focused Search of Neighbours

      • Najlaa Maaroof, Antonio Moreno, Aida Valls, Mohammed Jabreel
      Pages 49-62

    6. Interactive Natural Language Technology for Explainable Artificial Intelligence

      • Jose M. Alonso, Senén Barro, Alberto Bugarín, Kees van Deemter, Claire Gardent, Albert Gatt et al.
      Pages 63-70

    7. Hybrid AI: The Way Forward in AI by Developing Four Dimensions

      • Albert Huizing, Cor Veenman, Mark Neerincx, Judith Dijk
      Pages 71-76

    8. Towards Certifying Trustworthy Machine Learning Systems

      • Roland H. C. Yap
      Pages 77-82

    9. Lab Conditions for Research on Explainable Automated Decisions

      • Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns et al.
      Pages 83-90

  3. Paradigms

    1. Front Matter

      Pages 91-91
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    2. Assessment of Manifold Unfolding in Trained Deep Neural Network Classifiers

      • Štefan Pócoš, Iveta Bečková, Tomáš Kuzma, Igor Farkaš
      Pages 93-103

    3. Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms

      • Fredrik Präntare, Mattias Tiger, David Bergström, Herman Appelgren, Fredrik Heintz
      Pages 104-111

    4. An Analysis of Regularized Approaches for Constrained Machine Learning

      • Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano
      Pages 112-119

  4. Acting and Optimizing

    1. Front Matter

      Pages 121-121
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    2. Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art

      • Youngmin Kim, Richard Allmendinger, Manuel López-Ibáñez
      Pages 123-139

    3. A Causal Framework for Understanding Optimisation Algorithms

      • Alberto Franzin, Thomas Stützle
      Pages 140-145

    4. Uncertainty Quantification and Calibration of Imitation Learning Policy in Autonomous Driving

      • Farzad Nozarian, Christian Müller, Philipp Slusallek
      Pages 146-162

    5. Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning

      • Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé
      Pages 163-179

    6. Modelling Agent Policies with Interpretable Imitation Learning

      • Tom Bewley, Jonathan Lawry, Arthur Richards
      Pages 180-186
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  1. Trustworthy AI - Integrating Learning, Optimization and Reasoning

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About this book

This book constitutes the thoroughly refereed conference proceedings of the First International Workshop on the Foundation of Trustworthy AI - Integrating Learning, Optimization and Reasoning, TAILOR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence.

The 11 revised full papers presented together with 6 short papers and 6 position papers were reviewed and selected from 52 submissions. The contributions address various issues for Trustworthiness, Learning, reasoning, and optimization, Deciding and Learning How to Act, AutoAI,  and Reasoning and Learning in Social Contexts.

Editors and Affiliations

  • Department of Computer and Information Science, Linköping University, Linköping, Sweden

    Fredrik Heintz

  • ALMA-AI Research Institute on Human-Centered AI, University of Bologna, Bologna, Italy

    Michela Milano

  • Department of Computer Science, University College Cork, Cork, Ireland

    Barry O'Sullivan

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