Trustworthy Planning and Scheduling with Learning and Explanations

Informazioni relative al progetto

TUPLES

ID dell’accordo di sovvenzione: 101070149

DOI

10.3030/101070149

Progetto chiuso

Data della firma CE 12 Giugno 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2025

Finanziato da

• Digital, Industry and Space

Costo totale

€ 4 200 886,25

Contributo UE

€ 4 200 886,25

Coordinato da

LA COMMUNAUTE D UNIVERSITES ET ETABLISSEMENTS DE TOULOUSE
France

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Other (13)

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).

Software for interactive and approximate explanations

Software for interactive and approximate explanations (M30, Software).

Expl. ML models and systems of constraints

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

Scalable search methods integrating learning

Scalable search methods integrating policy/heuristic learning and improvement (M24, Software+Report)

Fram. for robustness verification of policies

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

Expl. policies in learning-based S&P

Explanations for action policies in learning-based scheduling and planning (M30, Report+Software).

Fram. for testing & verif. of policy behavior

Framework for testing and verification of policy-behavior (M24, Software).

Expl. policies in non-learning based P&S

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

GitHub/TUPLES lab - solving algorithms

Use cases' solving algorithms hosted on GitHub/TUPLES lab (M36, Software).

POC of applicability of LRNNs in P&S

POC of applicability of LRNNs in planning and scheudling (M24, Software+Report)

Methods for integration of LRNNs into P&S

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

TUPLES self-assessment tool - beta

Development and beta-release of the TUPLES self-assessment tool (M24, Software).

Documents, reports (11)

Environmental impact evaluation

Report on environmental impact evaluation (M36, Report).

Meth. for robustness verification of policies

Methods for robustness verification of policy-decisions (M24, Report).

Meth. for trustworthy P&S

Report on methodologies and guidelines for trustworthy planning and scheduling (M36, Report).

Interactive explanations and approximate explanations

Interactive explanations and approximate explanations (M24, Report).

Integrated online/offline (re-)scheduling

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

Robust constraint acquisition methods

Design and analysis of robust constraint acquisition methods, and neural network architectures for capturing the structure of planning and scheduling models (M24, Report).

Test for solvability by a NN architecture

Procedure testing wether a task is solvable by a neural network architecture (M24, report)

Final report on dissemination and communication activities

Final report on dissemination and communication activities (M36, Report).

Robust integration of learning and solving

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

Meth. for testing & verif. of policy behavior

Methods for testing and verification of policy-behavior (M36, Report).

Meth. learning with robustness guarantees

Methods for policy learning with decision-robustness guarantees (M24, Report).

Websites, patent fillings, videos etc. (1)

Competition results

Competition results posted on the website (M31, Website).

Demonstrators, pilots, prototypes (1)

Use case demonstrators hosted on GitHub

Use case demonstrators hosted on GitHub (M36, Software).

Pubblicazioni

Conference proceedings (56)

Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages

Autori: Timo P. Gros, Nicola J. Müller, Daniel Höller, Verena Wolf
Pubblicato in: Proceedings of the Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS), at ICAPS'24, 2024
Editore: http://fai.cs.uni-saarland.de/gros/papers/icaps24-RDDPS.pdf

Faster Robustness Verification by Exploiting Repeated Structure in Adversarial Examples

Autori: Lorenzo Cascioli, Laurens Devos, Jesse Davis
Pubblicato in: Proceedings of the ECAI Workshop on Verifying Learning AI Systems (VeriLearn'23), 2023

Faster Repeated Evasion Attacks in Tree Ensembles

Autori: Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis
Pubblicato in: Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 2024
Editore: Curran Associates, Inc.; https://papers.nips.cc/paper_files/paper/2024

Conversational Goal-Conflict Explanations in Planning via Multi-Agent LLMs

Autori: Guilhem Fouilhé, Rebecca Eifler, Antonin Poché, Sylvie Thiébaux, Nicholas Asher
Pubblicato in: Proceedings of the AAAI25 Workshop on Planning in the Era of LLMs (LM4Plan@AAAI-25), 2025
Editore: Openreview

Detecting Evasion Attacks in Deployed Tree Ensembles

Autori: Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
Pubblicato in: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD'23), 2023, ISBN 978-3-031-43424-2
Editore: Springer
DOI: 10.1007/978-3-031-43424-2_8

An Efficient Structured Perceptron for NP-Hard Combinatorial Optimization Problems

Autori: Bastián Véjar, Gaël Aglin, Ali İrfan Mahmutoğulları, Siegfried Nijssen, Pierre Schaus, Tias Guns
Pubblicato in: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60599-4_17

Learning Heuristics for Numeric Planning

Autori: Dillon Z Chen and Sylvie Thiebaux
Pubblicato in: Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS-24), 2024
Editore: Curran Associates

On Picking Good Policies: Leveraging Action-Policy Testing in Policy Training

Autori: Jan Eisenhut, Daniel Fišer, Isabel Valera, Jörg Hoffmann
Pubblicato in: Proceedings of the 35th International Conference on Automated Planning and Scheduling (ICAPS'25), 2025
Editore: AAAI Press

Action Policy Testing with Heuristic-Based Bias Functions

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

Multi-class Robustness Verification for Tree Ensembles

Autori: Laurens Devos, Lorenzo Cascioli, Jesse Davis
Pubblicato in: Proceedings of the ECAI Workshop on Verifying Learning AI Systems Workshop (VeriLearn'23), 2023

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Autori: Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
Pubblicato in: Proceedings of the ICAPS Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS'24), 2024, ISBN 978-1-64368-548-9
Editore: None
DOI: 10.3233/FAIA240614

Neural Policy Safety Verification via Predicate Abstraction: CEGAR

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

Simplifying Step-wise Explanation Sequences

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

Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches

Autori: Léo Boisvert, Hélène Verhaeghe, Quentin Cappart
Pubblicato in: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60597-0_7

Guided Bottom-Up Interactive Constraint Acquisition

Autori: Dimosthenis Tsouros, Senne Berden, Tias Guns
Pubblicato in: Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP'23), 2023, ISSN 1868-8969
Editore: Leibniz-Zentrum für Informatik
DOI: 10.48550/arXiv.2307.06126

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

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

Blossom: an Anytime Algorithm for Computing Optimal Decision Trees

Autori: Emir Demirović, Emmanuel Hebrard, Louis Jean
Pubblicato in: Proceedings of the 40th International Conference on Machine Learning (ICML'23), 2023
Editore: PMLR

Computational Asymmetries in Robust Classification

Autori: Samuele Marro, Michele Lombardi.
Pubblicato in: Proceedings of the 40th International Conference on Machine Learning (ICML'23), 2023
Editore: ICML
DOI: 10.48550/arXiv.2306.14326

Policy-Specific Abstraction Predicate Selection in Neural Policy Safety Verification

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

Is This a Good Decision? Action Optimality Checking in Classical Planning

Autori: Jan Eisenhut, Daniel Fišer, Wheeler Ruml, Jörg Hoffmann
Pubblicato in: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI'25), 2025
Editore: IOS Press

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

Autori: Marcel Steinmetz, Sylvie Thiébaux, Daniel Höller, and Florent Teichteil-Königsbuch
Pubblicato in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Editore: AAAI Press

Disjunctive Scheduling in Tempo

Autori: Emmanuel Hebrard
Pubblicato in: Proceedings of the 31st International Conference on Principles and Practice of Constraint Programming (CP-25)), 2025
Editore: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/LIPICS.CP.2025.13

Policy Safety Testing in Non-Deterministic Planning: Fuzzing, Test Oracles, Fault Analysis

Autori: Chaahat Jain, Daniel Sherbakov, Marcel Vinzent, Marcel Steinmetz, Jesse Davis and Jörg Hoffmann
Pubblicato in: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI'25), 2025
Editore: IOS Press

Learning to Learn in Interactive Constraint Acquisition

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

ReDeLEx: A Framework for Relational Deep Learning Exploration

Autori: Jakub Peleska, Gustav Sir
Pubblicato in: Lecture Notes in Artificial Intelligence, 2025
Editore: Springer

An Operator-Centric Trustable Decision-Making Tool for Planning Ground Logistic Operations of Beluga Aircraft

Autori: Rebecca Eifler, Nika Beriachvili, Arthur Bit-Monnot, Dillon Z. Chen, Jan Eisenhut, Joerg Hoffmann, Sylvie Thiébaux, and Florent Teichteil-Königsbuch
Pubblicato in: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI-25), Demonstration Track, 2025
Editore: IOS Press

Exploiting Symmetries in MUS Computation

Autori: Ignace Bleukx, Hélène Verhaeghe, Bart Bogaerts, Tias Guns
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I11.33209

Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem

Autori: Ignace Bleukx, Ryma Boumazouza, Tias Guns, Nadine Laage, Guillaume Poveda
Pubblicato in: Proceedings of the 31st International Conference on Principles and Practice of Constraint Programming (CP-25), 2025
Editore: Dagstuhl Publishing
DOI: 10.4230/LIPICS.CP.2025.6

Learning Domain-Independent Heuristics for Grounded and Lifted Planning

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

New Fuzzing Biases for Action Policy Testing

Autori: Jan Eisenhut, Xandra Schuler, Daniel Fišer, Daniel Höller, Maria Christakis, Jörg Hoffmann
Pubblicato in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Editore: AAAI Press

Guiding GBFS through Learned Pairwise Rankings

Autori: Mingyu Hao, Felipe Trevizan, Sylvie Thiebaux, Patrick Ferber and Jörg Hoffmann
Pubblicato in: Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), 2024
Editore: IJCAI Organization
DOI: 10.24963/ijcai.2024/743

SMLE: Safe Machine Learning via Embedded Overapproximation

Autori: Matteo Francobaldi, Michele Lombardi
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I26.34938

Understanding the Impact of Value Selection Heuristics in Scheduling Problems

Autori: Tim Luchterhand, Emmanuel Hebrard, Sylvie Thiébaux.
Pubblicato in: Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming (CP-25), 2025
Editore: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/LIPICS.CP.2025.27

Towards Feasible Higher-Dimensional Potential Heuristics

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

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

Autori: Rebecca Eiflera, Daniel Fišer, Aleena Siji, Jörg Hoffmann
Pubblicato in: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Editore: IOS Press

Effective Data Generation and Feature Selection in Learning for Planning

Autori: Mingyu Hao, Dillon Z. Chen, Felipe Trevizan, Sylvie Thiebaux
Pubblicato in: Proceedings of the 28th European Conference on Artificial Intelligence, 2025
Editore: IOS Press

Safety Verification of Tree-Ensemble Policies via Predicate Abstraction

Autori: Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann
Pubblicato in: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Editore: IOS Press

Automatic Metamorphic Test Oracles for Action-Policy Testing

Autori: Jan Eisenhut, Álvaro Torralba, Maria Christakis, Jörg Hoffmann
Pubblicato in: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS'23), 2023
Editore: AAAI Press
DOI: 10.1609/ICAPS.V33I1.27185

Learning Efficiency Meets Symmetry Breaking

Autori: Yingbin Bai, Sylvie Thiébaux, Felipe Trevizan
Pubblicato in: Proceedings of the 35th International Conference on Automated Planning and Scheduling, 2025
Editore: AAAI Press

Learning Precedences for Scheduling Problems with Graph Neural Networks

Autori: Hélène Verhaeghe, Quentin Cappart, Gilles Pesant, Claude-Guy Quimper
Pubblicato in: 30th International Conference on Principles and Practice of Constraint Programming (CP 2024), 2024
Editore: Leibniz International Proceedings in Informatics (LIPIcs)
DOI: 10.4230/LIPICS.CP.2024.30

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

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

Complexity of Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers: A Bound to Beat

Autori: Jan Tóth, Ondřej Kuželka
Pubblicato in: Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning, 2024, ISSN 2334-1033
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/KR.2024/64

Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning

Autori: Dillon Z. Chen, Felipe Trevizan, Sylvie Thiébaux
Pubblicato in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Editore: 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

Autori: Sofia Morandini, Federico Fraboni, Enzo Balatti, Aranka Hackmann, Hannah Brendel, Gabriele Puzzo, Lucia Volpi, Davide Giusino, Marco De Angelis, Luca Pietrantoni.
Pubblicato in: Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE'23), 2023
Editore: AHFE International
DOI: 10.54941/ahfe1004068

Decision-Focused Learning to Predict Action Costs for Planning

Autori: Jayanta Mandi, Marco Foschini, Daniel Höller, Sylvie Thiébaux, Jörg Hoffmann, Tias Guns
Pubblicato in: Proceedings of the 27th European Conference on Artificial Intelligence (ECAI'24), 2024
Editore: IOS Press

Explainability Insights to Cellular Simultaneous Recurrent Neural Networks for Classical Planning

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

State Encodings for GNN-Based Lifted Planners

Autori: Rostislav Horčik, Gustav Šír, Vítězslav Šimek, Tomáš Pevný
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I25.34853

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

Autori: Mattia Silvestri, Senne Berden, Jayanta Mandi, Ali Mahmutogullari, Maxime Mulamba, Allegra De Filippo, Tias Guns, Michele Lombardi
Pubblicato in: Proceedings of the ICML Workshop Differentiable Almost Everything workshop, 2023
DOI: 10.48550/arXiv.2307.05213

Robustness Verification of Multi-Class Tree Ensembles

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

Learning Generalised Policies for Numeric Planning

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

Expressiveness of Graph Neural Networks in Planning Domains

Autori: Rostislav Horcik, Gustav Sir
Pubblicato in: Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS'24), 2024
Editore: AAAI Press

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

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

Action Policy Explanations in Oversubscription Planning

Autori: Aleena Siji, Rebecca Eifler, Daniel Fišer, Jörg Hoffmann
Pubblicato in: Proceedings of the ICAPS Workshop on Human-Aware and Explainable Planning (HAXP'23), 2023
Editore: none

Fast and Robust Resource-Constrained Scheduling with Graph Neural Networks

Autori: Florent Teichteil-Koenigsbuch, Guillaume Poveda, Guillermo Gonzales de Garibay Barba, Tim Luchterhand, Sylvie Thiébaux
Pubblicato in: Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS'23), 2023
Editore: AAAI
DOI: 10.1609/icaps.v33i1.27244

Formal Explanations of Neural Network Policies for Planning

Autori: Renee Selvey, Alban Grastien, Sylvie Thiébaux
Pubblicato in: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 2023
Editore: IJCAI.org
DOI: 10.24963/ijcai.2023/605

A Deep Learning Blueprint for Relational Databases

Autori: Lukáš Zahradník, Jan Neumann, Gustav Šír
Pubblicato in: Proceedings of the NeurIPS Workshop on Table Representation Learning (TRL'23), 2023
Editore: none

Peer reviewed articles (11)

Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

Autori: Jayanta Mandi, James Kotary, Senne Berden, Maxime Mulamba, Victor Bucarey, Tias Guns, Ferdinando Fioretto
Pubblicato in: Journal of Artificial Intelligence Research, Numero 80, 2024, ISSN 1076-9757
Editore: AI Access Foundation
DOI: 10.1613/jair.1.15320

Machine Learning

Autori: Davis, Jesse; Bransen, Lotte; Devos, Laurens; Jaspers, Arne; Meert, Wannes; Robberechts, Pieter; Van Haaren, Jan; Van Roy, Maaike
Pubblicato in: Machine Learning, 2024, ISSN 0885-6125
Editore: Springer Verlag
DOI: 10.1007/s10994-024-06585-0

User perspectives on AI explainability in aerospace manufacturing: a Card-Sorting study

Autori: Morandini, Sofia; Fraboni, Federico; Hall, Mark; Quintana-Amate, Santiago; Pietrantoni, Luca
Pubblicato in: Frontiers in Organizational Psychology, 2025, ISSN 2813-771X
Editore: Frontiers
DOI: 10.3389/FORGP.2025.1538438

Knowledge-Based Systems

Autori: Mattia Silvestri; Allegra De Filippo; Michele Lombardi; Michela Milano
Pubblicato in: Knowledge-Based Systems, 2024, ISSN 0950-7051
Editore: Elsevier
DOI: 10.1016/J.KNOSYS.2024.112383

The TOAD System for Totally Ordered HTN Planning

Autori: Daniel Höller
Pubblicato in: Journal of Artificial Intelligence Research, Numero 80, 2024, ISSN 1076-9757
Editore: AI Access Foundation
DOI: 10.1613/JAIR.1.14945

Cognition, Technology and Work

Autori: Morandini, Sofia; Fraboni, Federico; Hall, Mark; Quintana-Amate, Santiago; Pietrantoni, Luca
Pubblicato in: Cognition, Technology & Work, 2024, ISSN 1435-5558
Editore: Springer Nature
DOI: 10.1007/S10111-024-00785-3

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

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

Complexity of minimum-size arc-inconsistency explanations

Autori: Bessiere, Christian; Carbonnel, Clément; Cooper, Martin C.; Hebrard, Emmanuel
Pubblicato in: Constraints, 2023, ISSN 1572-9354
Editore: Springer
DOI: 10.1007/S10601-023-09360-5

Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned

Autori: Davis, Jesse; Bransen, Lotte; Devos, Laurens; Jaspers, Arne; Meert, Wannes; Robberechts, Pieter; Van Haaren, Jan; Van Roy, Maaike
Pubblicato in: Machine Learning, 2024, ISSN 1573-0565
Editore: Springer
DOI: 10.1007/S10994-024-06585-0

A rolling horizon heuristic approach for a multi-stage stochastic waste collection problem

Autori: Andrea Spinelli, Francesca Maggioni, Tânia Rodrigues Pereira Ramos, Ana Paula Barbosa-Póvoa, Daniele Vigo
Pubblicato in: European Journal of Operational Research, Numero 323, 2025, ISSN 0377-2217
Editore: Elsevier BV
DOI: 10.1016/J.EJOR.2024.11.041

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

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

Book chapters (1)

Trustworthiness of AI in Planning and Scheduling: The Experience of the TUPLES Project

Autori: Angelo Gordini, Matteo Pozzi, Michele Lombardi, Thomas Sergeys, Tias Guns, Andrea De Cesarei, Sofia Morandini, Sylvie Thiébaux
Pubblicato in: Lecture Notes in Computer Science, Decision Sciences, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78241-1_30