H2020: TAILOR : Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

Research output

Research output per year 2020 2020 2021 2023

• 7 Article
• 3 Conference paper
• 1 Unpublished paper
• 1 Software

Research output per year

Research output per year

Search results

• 2023

  Dealing with Expert Bias in Collective Decision-Making

  Abels, A., Lenaerts, T., Trianni, V. & Nowe, A., Jul 2023, In: Artificial Intelligence. 320, 22 p., 103921.

  Research output: Contribution to journal › Article › peer-review

  • collective decision 100%
  • Decision making 54%
  • decision making 47%
  • expert 47%
  • Decision Making 42%
  2 Citations (Scopus)
• 2022

  Voluntary safety commitments provide an escape from over-regulation in AI development

  Han, T. A., Lenaerts, T., Santos, F. C. & Pereira, L. M., Feb 2022, In: Technology in Society. 68, 101843.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Soft Law 100%
  • Artificial Intelligence 86%
  • artificial intelligence 83%
  • Artificial intelligence 73%
  • Safety 67%
  21 Citations (Scopus)

  33 Downloads (Pure)
• 2021

  Mediating artificial intelligence developments through negative and positive incentives

  Han, T. A., Pereira, L. M., Lenaerts, T. & Santos, F. C., Jan 2021, In: PLOS ONE. 16, 1, 21 p., e0244592.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Artificial Intelligence 100%
  • Punishment 95%
  • Motivation 60%
  • Reward 48%
  • Safety 43%
  26 Citations (Scopus)

  70 Downloads (Pure)

• Modeling behavioral experiments on uncertainty and cooperation with population-based reinforcement learning

  Fernández Domingos, E., Grujić, J., Burguillo, J. C., Santos, F. C. & Lenaerts, T., May 2021, In: Simulation Modelling Practice and Theory. 109, 102299.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Behavioral Modeling 100%
  • Dilemma 76%
  • Reinforcement learning 54%
  • Uncertainty 46%
  • Experiment 41%
  10 Citations (Scopus)

  126 Downloads (Pure)

• Set-Valued Inductive Rule Learning

  Coppens, Y., 12 Feb 2021

  Research output: Non-textual form › Software

  Open Access

• Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning

  Coppens, Y., Steckelmacher, D., Jonker, C. M. & Nowe, A., 13 Apr 2021, Trustworthy AI - Integrating Learning, Optimization and Reasoning: First International Workshop, TAILOR 2020, Virtual Event, September 4–5, 2020, Revised Selected Papers. Heintz, F., Milano, M. & O'Sullivan, B. (eds.). 1 ed. Cham: Springer International Publishing, p. 163-179 17 p. (Lecture Notes in Computer Science; vol. 12641).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper

  Open Access

  • Reinforcement learning 100%
  • Set theory 64%
  • Learning algorithms 41%
  • Neural networks 15%
  2 Citations (Scopus)
• 2020

  Collective Decision-Making as a Contextual Multi-armed Bandit Problem

  Abels, A., Lenaerts, T., Trianni, V. & Nowé, A., Nov 2020, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, p. 113-124 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12496 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper

  • Decision making 100%

• Do people imitate when making decisions? Evidence from a spatial Prisoner's Dilemma experiment: Do people imitate when making decisions

  Grujic, J. & Lenaerts, T., 1 Jul 2020, In: ROYAL SOCIETY OPEN SCIENCE. 7, 7, p. 200618 11 p., 200618.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Prisoner Dilemma 100%
  • Game Theory 49%
  • Decision Making 48%
  15 Citations (Scopus)

  94 Downloads (Pure)

• How Expert Confidence Can Improve Collective Decision-Making in Contextual Multi-Armed Bandit Problems

  Abels, A., Lenaerts, T., Trianni, V. & Nowé, A., Nov 2020, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH, p. 125-138 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12496 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper

  • Decision making 100%
  2 Citations (Scopus)

• Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning

  Coppens, Y., Steckelmacher, D., Jonker, C. M. & Nowe, A., 4 Sep 2020. 16 p.

  Research output: Unpublished contribution to conference › Unpublished paper

  Open Access

  File

  • Reinforcement learning 100%
  • Set theory 64%
  • Learning algorithms 55%
  91 Downloads (Pure)

• Timing uncertainty in collective risk dilemmas encourages group reciprocation and polarization

  Domingos, E. F., Grujić, J., Burguillo, J. C., Kirchsteiger, G., Santos, F. C. & Lenaerts, T., 18 Dec 2020, In: iScience. 23, 12, p. 101752 51 p., 101752.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Uncertainty 100%
  • Climate 12%
  • Decision Making 8%
  • Theoretical Models 8%
  • Vaccination 8%
  31 Citations (Scopus)

  82 Downloads (Pure)

• To regulate or not: A social dynamics analysis of an idealised ai race

  Han, T. A., Pereira, L. M., Santos, F. C. & Lenaerts, T., 22 Nov 2020, In: Journal of Artificial Intelligence Research. 69, p. 881-921 41 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Dynamic analysis 100%
  • Artificial intelligence 97%
  • Ecology 22%
  • Compliance 16%
  • Costs 7%
  23 Citations (Scopus)

  90 Downloads (Pure)