About
Fredrik Heintz is Professor of Computer Science at Linköping University and founder and leader of the Reasoning and Learning (ReAL) Lab. He serves as Head of the AIICS Division, Director of WASP's Graduate School, Program Director of WASP-ED, Coordinator of the EU TAILOR network and TrustLLM project, and Director of LiU's AI initiative. He is one of Sweden's most prominent voices on AI in media.
Publications 61
2026
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2025
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2024
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FairX
Proceedings of the 2nd Workshop on Fairness and Bias in AI, co-located with 27th European Conference on Artificial Intelligence (ECAI 2024), Roberta Calegari,Virginia Dignum, Barry O’Sullivan (eds.), CEUR Workshop Proceedings, CEUR
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Exploratory Visual Analysis for Increasing Data Readiness in Artificial Intelligence Projects
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Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
2023
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Model-Based Multi-Objective Reinforcement Learning with Dynamic Utility Functions
Proceedings of the Adaptive and Learning Agents Workshop (ALA) at AAMAS 2023, pp. 1-9
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Model-Based Actor-Critic for Multi-Objective Reinforcement Learning with Dynamic Utility Functions
Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 2818-2820, International Foundation for Autonomous Agents and Multiagent Systems
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Introducing programming and computational thinking in grades 1–9
Programming and computational thinking in technology education, Jonas Hallström, Marc J. de Vries (eds.), pp. 60-88, Brill Academic Publishers, Leiden
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Four facets of AI transperency
Handbook of Critical Studies of Artificial Intelligence, Simon Lindgren (ed.), pp. 445-455, Edward Elgar Publishing, Cheltenham
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A Brief Guide to Multi-Objective Reinforcement Learning and Planning
Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), A. Ricci, W. Yeoh, N. Agmon, B. An (eds.), pp. 1988-1990
2022
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2021
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Towards Verification and Validation of Reinforcement Learning in Safety-Critical Systems
Robust and Reliable Autonomy in the Wild
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Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton
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Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment
THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, Proceedings of the AAAI Conference on Artificial Intelligence, pp. 11317-11324, ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE
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Achieving a Data-driven Risk Assessment Methodology for Ethical AI
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2020
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Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
Trustworthy AI - Integrating Learning, Optimization and Reasoning, Fredrik Heintz, Michela Milano, Barry O’Sullivan (eds.), Lecture Notes in Computer Science, pp. 104-111, Springer, Cham, Germany
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Spatio-Temporal Learning, Reasoning and Decision-Making with Robot Safety Applications
Proceedings of the 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS 2020), Fredrik Johansson (ed.), Göteborg
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Learning Agents for Improved Efficiency and Effectiveness in Simulation-Based Training
Poceedings of the 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS), pp. 1-2
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Commentary on AI in the EU
Human-centred AI in the EU, Stefan Larsson, Claire Ingram Bogusz and Jonas Andersson Schwarz (eds.), pp. 1-12, European Liberal Forum (ELF)
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2nd International Workshop on Education in Artificial Intelligence K-12 (EduAI)
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2020), PT II, Lecture Notes in Artificial Intelligence, pp. 427-429, SPRINGER INTERNATIONAL PUBLISHING AG