Trustworthy Planning and Scheduling with Learning and Explanations

Leistungen

GitHub/TUPLES lab - simulators & planning domains

Use case simulators and planning domains hosted on GitHub/TUPLES lab (M18, Software).

Fram. learning with robustness guarantees

Framework for policy learning with decision-robustness guarantees (M18, Software).

Expl. ML models and systems of constraints

Explanations for ML models and systems of constraints (M12, Report+Software).

Fram. for robustness verification of policies

Framework for robustness verification of policy-decisions (M18, Software).

Expl. policies in non-learning based P&S

Explanations for action policies in non-learning based scheduling and planning (M18, Report+Software).

Methods for integration of LRNNs into P&S

Methods for integration of LRNNs into planning and scheduling domains (M18, software, report)

Integrated online/offline (re-)scheduling

Integrated offline/online scheduling and rescheduling solutions (M18, Report).

Robust integration of learning and solving

Robust integrated learning and solving with predicted costs (M18, Report).

Veröffentlichungen

Adversarial Example Detection in Deployed Tree Ensembles

Autoren: Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
Veröffentlicht in: Machine Learning and Knowledge Discovery in Databases; 2023, 2023
Herausgeber: Springer
DOI: 10.48550/arXiv.2206.13083

Action Policy Testing with Heuristic-Based Bias Functions

Autoren: Xandra Schuler, Jan Eisenhut, Daniel Höller, Daniel Fišer and Jörg Hoffmann
Veröffentlicht in: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'23), 2023
Herausgeber: none

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Autoren: Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
Veröffentlicht in: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'24), 2024
Herausgeber: None

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

Autoren: Marcel Vinzent, Siddhant Sharma, Jörg Hoffmann
Veröffentlicht in: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI'23), 2023, ISSN 2374-3468
Herausgeber: AAAI Press
DOI: 10.1609/aaai.v37i12.26772

Simplifying Step-wise Explanation Sequences

Autoren: Ignace Bleukx, Jo Devriendt, Emilio Gamba, Bart Bogaerts, Tias Guns
Veröffentlicht in: Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP'23), 2023, ISSN 1868-8969
Herausgeber: Leibniz-Zentrum für Informatik

Guided Bottom-Up Interactive Constraint Acquisition

Autoren: Dimosthenis Tsouros, Senne Berden, Tias Guns
Veröffentlicht in: Leibniz International Proceedings in Informatics; 2023, 2023, ISSN 1868-8969
Herausgeber: Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
DOI: 10.48550/arXiv.2307.06126

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

Autoren: Leah Chrestien, Stefan Edelkamp, Antonin Komenda, Tomas Pevny
Veröffentlicht in: Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS'23), 2023
Herausgeber: none

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

Autoren: Emir Demirović, Emmanuel Hebrard, Louis Jean
Veröffentlicht in: Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
Herausgeber: PMLR

Computational Asymmetries in Robust Classification

Autoren: Samuele Marro, Michele Lombardi.
Veröffentlicht in: 40th International Conference on Machine Learning (ICML 2023), 2023
Herausgeber: ICML
DOI: 10.48550/arXiv.2306.14326

Policy-Specific Abstraction Predicate Selection in Neural Policy Safety Verification

Autoren: Marcel Vinzent, Min Wu, Haoze Wu, Jörg Hoffmann
Veröffentlicht in: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'23), 2023
Herausgeber: none

Learning to Learn in Interactive Constraint Acquisition

Autoren: Dimosthenis Tsouros, Senne Berden, Tias Guns
Veröffentlicht in: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Herausgeber: AAAI Press, Washington, DC, USA
DOI: 10.1609/aaai.v38i8.28655

Learning Domain-Independent Heuristics for Grounded and Lifted Planning

Autoren: Dillon Z. Chen, Sylvie Thiébaux, Felipe Trevizan
Veröffentlicht in: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Herausgeber: AAAI Press
DOI: 10.1609/aaai.v38i18.29986

Guiding GBFS through Learned Pairwise Rankings

Autoren: Mingyu Hao, Felipe Trevizan, Sylvie Thiebaux, Patrick Ferber and Jörg Hoffmann
Veröffentlicht in: Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), 2024
Herausgeber: IJCAI Organization

Towards Feasible Higher-Dimensional Potential Heuristics

Autoren: Daniel Fiser, Marcel Steinmetz
Veröffentlicht in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Herausgeber: AAAI Press

Automatic Metamorphic Test Oracles for Action-Policy Testing

Autoren: Jan Eisenhut, Álvaro Torralba, Maria Christakis, Jörg Hoffmann
Veröffentlicht in: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS'23), 2023
Herausgeber: AAAI Press
DOI: 10.1609/icaps.v33i1.27185

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

Autoren: Dillon Z. Chen, Sylvie Thiébaux
Veröffentlicht in: Proceedings of the 17th International Symposium on Combinatorial Search (SOCS'24), 2024
Herausgeber: AAAI Press
DOI: 10.48550/arXiv.2404.05235

Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning

Autoren: Dillon Z. Chen, Felipe Trevizan, Sylvie Thiébaux
Veröffentlicht in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Herausgeber: AAAI Press
DOI: 10.1609/icaps.v34i1.31462

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

Autoren: Sofia Morandini, Federico Fraboni, Enzo Balatti, Aranka Hackmann, Hannah Brendel, Gabriele Puzzo, Lucia Volpi, Davide Giusino, Marco De Angelis, Luca Pietrantoni.
Veröffentlicht in: AHFE (2023) International Conference, 2023
Herausgeber: AHFE International
DOI: 10.54941/ahfe1004068

Explainability Insights to Cellular Simultaneous Recurrent Neural Networks for Classical Planning

Autoren: Michaela Urbanovská, Antonín Komenda
Veröffentlicht in: Proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART'24), Ausgabe Volume 3, 2024, ISSN 2184-433X
Herausgeber: SciTePress
DOI: 10.5220/0012375800003636

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

Autoren: Mattia Silvestri, Senne Berden, Jayanta Mandi, Ali Mahmutogullari, Maxime Mulamba, Allegra De Filippo, Tias Guns, Michele Lombardi
Veröffentlicht in: Differentiable Almost Everything workshop @ICML 2023, 2023
DOI: 10.48550/arXiv.2307.05213

Robustness Verification of Multi-Class Tree Ensembles

Autoren: Laurens Devos, Lorenzo Cascioli, Jesse Davis
Veröffentlicht in: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024, ISSN 2159-5399
Herausgeber: AAAI Press, Washington, DC, USA
DOI: 10.1609/aaai.v38i19.30093

Learning Generalised Policies for Numeric Planning

Autoren: Ryan Xiao Wang, Sylvie Thiébaux
Veröffentlicht in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (CAPS'24), 2024
Herausgeber: AAAI Press

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

Autoren: Gregor Behnke; Marcel Steinmetz
Veröffentlicht in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Herausgeber: AAAI Press

Action Policy Explanations in Oversubscription Planning

Autoren: Aleena Siji, Rebecca Eifler, Daniel Fišer, Jörg Hoffmann
Veröffentlicht in: Proceedings of the ICAPS Workshop on Human-Aware and Explainable Planning (HAXP), 2023
Herausgeber: none

Fast and robust resource - constrained scheduling with graph Neural Networks

Autoren: Teichteil-Koenigsbuch, F., Poveda,g., Gonzales de Garibay Barba, G., Luchterhand, T. and Thiébaux, S.
Veröffentlicht in: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS), 2023
DOI: 10.1609/icaps.v33i1.27244

Formal Explanations of Neural Network Policies for Planning

Autoren: Renee Selvey, Alban Grastien, Sylvie Thiébaux
Veröffentlicht in: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2023, 2023
Herausgeber: IJCAI.org
DOI: 10.24963/ijcai.2023/605

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

Autoren: Maaike Van Roy, Peter Robberechts, Wen Chi Yang, Luc De Raedt, Jesse Davis
Veröffentlicht in: Journal Of Artificial Intelligence Research, Ausgabe 77, 2023, ISSN 1076-9757
Herausgeber: Morgan Kaufmann Publishers, Inc.
DOI: 10.1613/jair.1.13934

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

Autoren: Francesco Cavaliere, Luca Accorsi, Demetrio Laganà, Roberto Musmanno, Daniele Vigo
Veröffentlicht in: Transportation Research Part E: Logistics and Transportation Review, Ausgabe Volume 186, June 2024, 2024, ISSN 1878-5794
Herausgeber: Elsevier
DOI: 10.1016/j.tre.2024.103550

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