Publications

The first objective of TUPLES is to advance the scientific state of the art in the field of Trustworthy AI and its application in the design and management of safe, robust, scalable and explainable Planning & Scheduling decision support systems and tools.The original contributions produced by the TUPLES consortium partners, as part of the project, will be linked below, as soon as they are published.

Publications

Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal

Leah Chrestien, Stefan Edelkamp, Antonin Komenda, Tomas Pevny

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NeurIPS 2023, Annual Conference on Neural Information Processing Systems

Multi-class Robustness Verification for Tree Ensembles

Laurens Devos, Lorenzo Cascioli, Jesse Davis
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Proceedings of the Verifying Learning AI Systems Workshop; 2023

Guided Bottom-Up Interactive Constraint Acquisition

Dimosthenis Tsouros, Senne Berden, Tias Guns
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Leibniz International Proceedings in Informatics; 2023

Faster Robustness Verification by Exploiting Repeated Structure in Adversarial Examples

Lorenzo Cascioli, Laurens Devos, Jesse Davis
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Proceedings of Verifying Learning AI Systems Workshop; 2023

Simplifying Step-wise Explanation Sequences

Authors: Ignace Bleukx, Jo Devriendt, Emilio Gamba, Bart Bogaerts, Tias Guns
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Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP), 2023

Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning

Authors: Mattia Silvestri, Senne Berden, Jayanta Mandi, Ali Mahmutogullari, Maxime Mulamba, Allegra De Filippo, Tias Guns, Michele Lombardi
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Differentiable Almost Everything workshop at the International Conference on Machine Learning (ICML), 2023

Detecting Evasion Attacks in Deployed Tree Ensembles

Authors: Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
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Machine Learning and Knowledge Discovery in Databases (ECML PKDD) Springer Nature Switzerland, 2023

A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer

Authors: Maaike Van Roy, Peter Robberechts, Wen Chi Yang, Luc De Raedt, Jesse Davis
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Journal Of Artificial Intelligence Research, Vol. 77, 2023

Formal Explanations of Neural Network Policies for Planning

Authors: Renee Selvey, Alban Grastien, Sylvie Thiébaux
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Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2023

Computational Asymmetries in Robust Classification

Authors: Samuele Marro, Michele Lombardi
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40th International Conference on Machine Learning (ICML) 2023

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

Authors: Emir Demirović, Emmanuel Hebrard, Louis Jean
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Proceedings of the 40th International Conference on Machine Learning (ICML) 2023

Assessing the Transparency and Explainability of AI Algorithms in Planning and Scheduling Tools: A Review of the Literature

Authors: Sofia Morandini, Federico Fraboni, Enzo Balatti, Aranka Hackmann, Hannah Brendel, Gabriele Puzzo, Lucia Volpi, Davide Giusino, Marco De Angelis, Luca Pietrantoni
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AHFE (2023) International Conference

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

Authors: Marcel Vinzent, Siddhant Sharma, Jörg Hoffmann
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Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) 2023

Action Policy Testing with Heuristic-Based Bias Functions

Authors: Xandra Schuler, Jan Eisenhut, Daniel Höller, Daniel Fišer and Jörg Hoffmann
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Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS) 2023

Automatic Metamorphic Test Oracles for Action-Policy Testing

Authors: Jan Eisenhut, Álvaro Torralba, Maria Christakis, Jörg Hoffmann
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Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS), 2023

Policy-Specific Abstraction Predicate Selection in Neural Policy Safety Verification

Authors: Marcel Vinzent, Min Wu, Haoze Wu, Jörg Hoffmann
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Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), 2023

Action Policy Explanations in Oversubscription Planning

Authors: Aleena Siji, Rebecca Eifler, Daniel Fišer, Jörg Hoffmann
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Proceedings of the ICAPS Workshop on Human-Aware and Explainable Planning (HAXP) 2023

Fast and robust resource-constrained scheduling with graph Neural Networks

Authors: Florent Teichteil-Koenigsbuch, Guillaume Poveda, Guillermo Gonzales de Garibay Barba, Tim Luchterhand, Sylvie Thiébaux
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Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS) 2023

Keynotes & Seminars

Reasoning about Tree Ensembles

Jesse Davis is a keynote speaker at the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2023) in Arras (France), September 2023.
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Perception-based solving with CPMpy

By Tias Guns at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming.
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Welcome and Intro to Constraint Programming

By Tias Guns at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming
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Rambling Away from Decision-Focused Learning

By Michele Lombardi at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming
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Constraint Acquisition: Learning Constraint Models from Data

Constraint Acquisition: Learning Constraint Models from Data by Dimos Tsouros at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming.
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Optimisation in Machine Learning

Invited talk on “Optimisation in Machine Learning” by Tias Guns at VAIA, June 2023.
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Measuring Passing Creativity in Soccer

Invited talk on “Measuring Passing Creativity in Soccer” by Jesse Davis at the World Congress on Science and Football, Groningen. May 2023.
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Learning from user and environment in combinatorial optimisation

Invited talk “Learning from user and environment in combinatorial optimisation”by Tias Guns at IPAM workshop. Feb 2023
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Predict and Optimize

Invited seminar by Tias Guns on “Predict and Optimize: combinatorial optimisation with machine-learning based input” at VAIA (Flemish AI Academy). March 2023.
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Conferences & Workshop

Workshop on Reliable Data-Driven Planning and Scheduling 2024

RDDPS Workshop at the 34th International Conference on Automated Planning and Scheduling ICAPS.

Organizers: Daniel Höller, Jörg Hoffmann, Marcel Steinmetz and Sylvie Thiebaux, are among the organizers

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VeriLearn

The Verifying Learning AI Systems (VeriLearn) workshop at the 26th European Conference on Artificial Intelligence (ECAI23)
Co-organizer: Prof. Jesse Davis
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HPlan

ICAPS Workshop on Hierarchical Planning (HPlan)
Co-organizer: Daniel Höller
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HAXP 2023

HAXP @ ICAPS 2023. International Workshop on Human-Aware and Explainable Planning (HAXP)
Co-organizer: Rebecca Eifler
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SMiLe 2023

Spring workshop on Mining and Learning 2023 (SMiLe 2023) in Sint-Michielgestel, Netherlands.
Co-organizers: Prof. Jesse Davis, Prof. Tias Guns
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10th Annual Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA)

In conjunction with ECMLPKDD 2023 (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery).
Co-organizer: Prof. Jesse Davis
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ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming

KU Leuven University.
Co-organizer: Prof. Tias Guns
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Reliable Data-Driven Planning and Scheduling (RDDPS)

Workshop @ ICAPS
Organizers: Jesse Davis, Daniel Höller, Jörg Hoffmann, Michele Lombardi, Sylvie Thiebaux
Link

Publications

Publications

Keynotes & Seminars

Conferences & Workshop

ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming

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