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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

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1 - 6 of 39 posts

Methodology and Evaluation in Sports Analytics: Challenges, Approaches and Lesson Learned

Machine Learning. Volume 113, pages 6977–7010

Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages

Proceedings of the Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), at ICAPS’24

Iterative Oversubscription Planning with Goal-Conflict Explanations: Scaling Up Through Policy-Guidance Approximation

Proceedings of the 27th European Conference on Artificial Intelligence (ECAI’24)

Guiding GBFS through Learned Pairwise Rankings

Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI’24)

Expressiveness of Graph Neural Networks in Planning Domains

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

Decision-Focused Learning to Predict Action Costs for Planning

Proceedings of the 27th European Conference on Artificial Intelligence (ECAI’24)

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

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

Towards Feasible Higher-Dimensional Potential Heuristics

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

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

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

Robustness Verification of Multi-Class Tree Ensembles

Proceedings of the AAAI Conference on Artificial Intelligence

Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning

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

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

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

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

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

New Fuzzing Biases for Action Policy Testing

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

Learning to Learn in Interactive Constraint Acquisition

Proceedings of the AAAI Conference on Artificial Intelligence

Learning domain-independent heuristics for grounded and lifted planning

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

Learning Generalised Policies for Numeric Planning

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

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

Explainability Insights to Cellular Simultaneous Recurrent Neural Networks for Classical Planning

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

A Deep Learning Blueprint for Relational Databases

NeurIPS 2023 Second Table Representation Learning Workshop

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

NeurIPS 2023, Annual Conference on Neural Information Processing Systems

Multi-class Robustness Verification for Tree Ensembles

Proceedings of the Verifying Learning AI Systems Workshop; 2023

Guided Bottom-Up Interactive Constraint Acquisition

Leibniz International Proceedings in Informatics; 2023

Faster Robustness Verification by Exploiting Repeated Structure in Adversarial Examples

Proceedings of Verifying Learning AI Systems Workshop; 2023

Complexity of minimum-size arc-inconsistency explanations

Constraints – An International Journal

Simplifying Step-wise Explanation Sequences

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

Differentiable Almost Everything workshop at the International Conference on Machine Learning (ICML), 2023

Detecting Evasion Attacks in Deployed Tree Ensembles

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

Journal Of Artificial Intelligence Research, Vol. 77, 2023

Formal Explanations of Neural Network Policies for Planning

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

Computational Asymmetries in Robust Classification

40th International Conference on Machine Learning (ICML) 2023

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

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

AHFE (2023) International Conference

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) 2023

Action Policy Testing with Heuristic-Based Bias Functions

Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS) 2023

Automatic Metamorphic Test Oracles for Action-Policy Testing

Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS), 2023

Policy-Specific Abstraction Predicate Selection in Neural Policy Safety Verification

Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), 2023

Action Policy Explanations in Oversubscription Planning

Proceedings of the ICAPS Workshop on Human-Aware and Explainable Planning (HAXP) 2023

Fast and robust resource-constrained scheduling with graph Neural Networks

Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS) 2023

Keynotes & Seminars

Workshop on Hierarchical Planning (HPlan). ICAPS ’24

Invited talk by Daniel Höller at the 7th ICAPS Workshop on Hierarchical Planning (HPlan 2024). Banff, Alberta, Canada

Link

Explanation techniques for CP. ACP 24

Tias Guns, “Explanation techniques for CP”, talk at ACP winter school 2024, March 2024

Link

Computational Approaches to Strategies and Tactic

The Computational Approaches to Strategies and Tactics in Sports. Dagstuhl seminar (Feb 18-23, 2024). Organized by Jesse Davis.

Link

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

From data to decisions: Combinatorial optimisation with learned inputs

Math+ TES 2023 summer school talk by Tias Guns.

link

Integrating Constraint Programming with Machine Learning and Explanations: The Sudoku Assistant App (and CPMpy)

Invited talk by Tias Guns at PTHG-23: The Sixth Workshop on Progress Towards the Holy Grail. A CP 2023 Workshop. August 2023

Link

Solving Complex Problems: Graphs, Constraints, and Machine Learning in Action. CP 2023

Hélène Verhaeghe, “Solving Complex Problems: Graphs, Constraints, and Machine Learning in Action”, invited talk at Constraint Modeling and Reformulation workshop, 2023

Link

Using AI to Analyze Player’s In Game Performances, VAIA event

Jesse DAvis at VAIA event on “Met AI naar het WK voetbal” Oct 22. Data and AI can help footballers and coaches achieve better performances, both at professional level and in amateur competitions.

Link

Conferences & Workshop

Scikit-Decide Library Tutorial at ICAPS’24

A Hands-On Tutorial on Scikit-Decide, the Open-Source C++ and Python Library for Planning, Scheduling and Reinforcement Learning. Florent Teichteil-Koenigsbuch, Guillaume Poveda, Sylvie Thiebaux and others.

Bridging the Gap Between Planning and Reinforcement Learning(PRL)

Marcel Steinmetz is co-organising the ICAPS’24 workshop on Bridging the Gap Between Planning and Reinforcement Learning (PRL)
Link

Trustworthy AI: Landscaping verifiable robustness. Adra-e Webinar

This event is in the context of ADRA-e Birds of a Feather webinar series which aims to provide insights into Research and Innovation Actions (RIAs) projects to foster collaboration and avail a joint platform for debate and results-sharing in AI, Data and Robotics.

5th Workshop on Explainable Logic-Based Knowledge Representation

21st International Conference on Principles of Knowledge Representation and Reasoning, Hanoi, Vietnam. XLoKR 2024

Jörg Hoffmann, Saarland University is in the Organization Committe

Link

Human-Aware and Explainable Planning (HAXP 24)

ICAPS’24 Workshop. Organizing Committee – Rebecca Eifler | LAAS-CNRS

Steering Committee – Jörg Hoffmann| Saarland University

link

Reliable Data-Driven Planning and Scheduling (RDDPS 24)

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

Explainable Constraint Solving Tutorial @ CP 2023

A Hands-On Tutorial at CP 2023, Toronto, Canada by Tias Guns, Ignace Bleukx and Dimos Tsouros

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 (RDDPS23)

Workshop @ ICAPS23
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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