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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
KEYNOTES & SEMINARS
CONFERENCES & WORKSHOPS

Publications

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1 - 6 of 32 posts

An efficient heuristic for very large-scale vehicle routing problems with simultaneous pickup and delivery

Francesco Cavaliere, Luca Accorsi, Demetrio Laganà, Roberto Musmanno, Daniele Vigo

Transportation Research Part E: Logistics and Transportation Review, Volume 186, June 2024

Towards Feasible Higher-Dimensional Potential Heuristics

Daniel Fiser, Marcel Steinmetz

Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS-24)

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann

Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS)

Robustness Verification of Multi-Class Tree Ensembles

Laurens Devos, Lorenzo Cascioli, Jesse Davis

Proceedings of the AAAI Conference on Artificial Intelligence

Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning

Dillon Z. Chen, Felipe Trevizan, Sylvie Thiébaux

Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS-24)

On the Computational Complexity of Stackelberg Planning and Meta-Operator Verification

Gregor Behnke; Marcel Steinmetz

34th International Conference on Automated Planning and Scheduling (ICAPS-24)

Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning

Dillon Z. Chen, Sylvie Thiébaux

Proceedings of the 17th International Symposium on Combinatorial Search (SOCS-24)

New Fuzzing Biases for Action Policy Testing

Jan Eisenhut, Xandra Schuler, Daniel Fišer, Daniel Höller, Maria Christakis, Jörg Hoffmann

Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS’24)

Learning to Learn in Interactive Constraint Acquisition

Dimosthenis Tsouros, Senne Berden, Tias Guns

Proceedings of the AAAI Conference on Artificial Intelligence

Learning domain-independent heuristics for grounded and lifted planning

Dillon Z. Chen, Sylvie Thiébaux, Felipe Trevizan

Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24)

Learning Generalised Policies for Numeric Planning

Ryan Xiao Wang, Sylvie Thiébaux

Proceedings of the 34th International Conference on Automated Planning and Scheduling (CAPS-24)

Explaining the Space of SSP Policies via Policy-Property Dependencies: Complexity, Algorithms, and Relation to Multi-Objective Planning

Marcel Steinmetz, Sylvie Thiébaux, Daniel Höller, and Florent Teichteil-Königsbuch

Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS’24)

Explainability Insights to Cellular Simultaneous Recurrent Neural Networks for Classical Planning

Michaela Urbanovská, Antonín Komenda

Proceedings of the 16th International Conference on Agents and Artificial Intelligence – Volume 3: ICAART

A Deep Learning Blueprint for Relational Databases

L. Zahradník, J. Neumann, G. Šír

NeurIPS 2023 Second Table Representation Learning Workshop

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

Leah Chrestien, Stefan Edelkamp, Antonin Komenda, Tomas Pevny

NeurIPS 2023, Annual Conference on Neural Information Processing Systems

Multi-class Robustness Verification for Tree Ensembles

Laurens Devos, Lorenzo Cascioli, Jesse Davis

Proceedings of the Verifying Learning AI Systems Workshop; 2023

Guided Bottom-Up Interactive Constraint Acquisition

Dimosthenis Tsouros, Senne Berden, Tias Guns

Leibniz International Proceedings in Informatics; 2023

Faster Robustness Verification by Exploiting Repeated Structure in Adversarial Examples

Lorenzo Cascioli, Laurens Devos, Jesse Davis

Proceedings of Verifying Learning AI Systems Workshop; 2023

Simplifying Step-wise Explanation Sequences

Authors: Ignace Bleukx, Jo Devriendt, Emilio Gamba, Bart Bogaerts, Tias Guns

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

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
Link

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

Journal Of Artificial Intelligence Research, Vol. 77, 2023

Formal Explanations of Neural Network Policies for Planning

Authors: Renee Selvey, Alban Grastien, Sylvie Thiébaux

Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2023

Computational Asymmetries in Robust Classification

Authors: Samuele Marro, Michele Lombardi

40th International Conference on Machine Learning (ICML) 2023

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

Authors: Emir Demirović, Emmanuel Hebrard, Louis Jean

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

AHFE (2023) International Conference

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

Authors: Marcel Vinzent, Siddhant Sharma, Jörg Hoffmann

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

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

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

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

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

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.
Link

Perception-based solving with CPMpy

By Tias Guns at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming.
Link

Welcome and Intro to Constraint Programming

By Tias Guns at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming
Link

Rambling Away from Decision-Focused Learning

By Michele Lombardi at the ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming
Link

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.
Link

Optimisation in Machine Learning

Invited talk on “Optimisation in Machine Learning” by Tias Guns at VAIA, June 2023.
Link

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.
Link

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
Link

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.
Link

 

 

Conferences & Workshop

KR’24 5th Workshop on Explainable Logic-Based Knowledge Representation

The workshop will be featured in the 21st International Conference on Principles of Knowledge Representation and Reasoning
Hanoi, Vietnam

Jörg Hoffmann, Saarland University is in the Organization Committe

Link

ICAPS’24 Workshop on Human-Aware and Explainable Planning (HAXP)

Organizing Committee – Rebecca Eifler | LAAS-CNRS

Steering Committee – Jörg Hoffmann| Saarland University

link

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

Link

VeriLearn

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

HPlan

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

HAXP 2023

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

SMiLe 2023

Spring workshop on Mining and Learning 2023 (SMiLe 2023) in Sint-Michielgestel, Netherlands.
Co-organizers: Prof. Jesse Davis, Prof. Tias Guns
Link

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
Link

ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming

KU Leuven University.
Co-organizer: Prof. Tias Guns
Link

Reliable Data-Driven Planning and Scheduling (RDDPS)

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

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TRUSTWORTHY AI

european project

This project has received funding from the European Union’s HORIZON-CL4-2021-HUMAN-01 research and innovation programme under grant agreement No. 101070149

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