Epistemic AI

Información del proyecto

E-pi

Identificador del acuerdo de subvención: 964505

DOI

10.3030/964505

Fecha de la firma de la CE 17 Diciembre 2020

Fecha de inicio 1 Marzo 2021

Fecha de finalización 28 Febrero 2026

Financiado con arreglo a

• EXCELLENT SCIENCE - Future and Emerging Technologies (FET)

Coste total

€ 3 016 618,75

Aportación de la UE

€ 3 016 618,75

Coordinado por

OXFORD BROOKES UNIVERSITY
United Kingdom

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (6)

Report on epistemic reinforcement learning, with codebase
Report on pointwise optimisation under epistemic uncertainty
Report on methods from uncertainty theory
Report on epistemic learning theory
Report on use case definition
Report on set-based learning

Websites, patent fillings, videos etc. (2)

Thematic workshop no 1
Website and project logo

Project website and logo are finalised

Other (1)

Report on epistemic unsupervised learning, with code

Publicaciones

Peer reviewed articles (7)

DeepSmoke: Deep learning model for smoke detection and segmentation in outdoor environments

Autores: Salman Khan; Salman Khan; Khan Muhammad; Tanveer Hussain; Javier Del Ser; Fabio Cuzzolin; Siddhartha Bhattacharyya; Zahid Akhtar; Victor Hugo C. de Albuquerque
Publicado en: Expert Systems with Applications, 2021, Página(s) 115-125, ISSN 0957-4174
Editor: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2021.115125

ROAD-R: the autonomous driving dataset with logical requirements

Autores: Eleonora Giunchiglia, Mihaela Cătălina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz
Publicado en: Machine Learning, Edición 112, 2023, Página(s) 3261-3291, ISSN 0885-6125
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10994-023-06322-z

Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning

Autores: Izaak L. Geursen, Bruno F. Santos, Neil Yorke-Smith
Publicado en: Journal of Air Transport Management, Edición 109, 2023, Página(s) 102397, ISSN 0969-6997
Editor: Pergamon Press Ltd.
DOI: 10.1016/j.jairtraman.2023.102397

Uncertainty measures: A critical survey

Autores: Fabio Cuzzolin
Publicado en: Information Fusion, Edición 114, 2024, Página(s) 102609, ISSN 1566-2535
Editor: Elsevier BV
DOI: 10.1016/j.inffus.2024.102609

Berth planning and real-time disruption recovery: a simulation study for a tidal port

Autores: Jaap-Jan van der Steeg, Menno Oudshoorn, Neil Yorke-Smith
Publicado en: Flexible Services and Manufacturing Journal, Edición 35, 2023, Página(s) 70-110, ISSN 1936-6582
Editor: Springer Pub. Co.,
DOI: 10.1007/s10696-022-09473-8

Theory of Mind and Preference Learning at the Interface of Cognitive Science, Neuroscience, and AI: A Review

Autores: Christelle Langley, Bogdan-Ionut Cirstea, Fabio Cuzzolin and Barbara J. Sahakian
Publicado en: Frontiers in Artificial Intelligence, Edición April 5 2022, 2022, ISSN 2624-8212
Editor: Frontiers Media S.A.
DOI: 10.3389/frai.2022.778852

ROAD: The ROad event Awareness Dataset for autonomous Driving

Autores: Gurkirt Singh, Stephen Akrigg, Manuele Di Maio, Valentina Fontana, Reza Javanmard Alitappeh, Suman Saha, Kossar Jeddisaravi, Farzad Yousefi, Jacob Culley, Tom Nicholson, Jordan Omokeowa, Salman Khan, Stanislao Grazioso, Andrew Bradley, Giuseppe Di Gironimo, Fabio Cuzzolin
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ISSN 1939-3539
Editor: IEEE
DOI: 10.1109/tpami.2022.3150906

Other (14)

Generalising realisability in statistical learning theory under epistemic uncertainty

Autores: F. Cuzzolin
Publicado en: arXiv preprint arXiv:2402.14759, Edición 22 Feb 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2402.14759

An introduction to optimization under uncertainty -- A short survey

Autores: Shariatmadar, Keivan; Wang, Kaizheng; Hubbard, Calvin R.; Hallez, Hans; Moens, David
Publicado en: arXiv report arxiv.2212.00862, Edición 1 Dec 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2212.00862

Credal learning theory

Autores: M. Caprio, M. Sultana, E. Elia and F. Cuzzolin
Publicado en: arXiv preprint arXiv:2402.00957, Edición 2 May 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2402.00957

Reasoning with random sets: An agenda for the future

Autores: F. Cuzzolin
Publicado en: arXiv preprint arXiv:2401.09435, Edición 19 Dec 2023, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2401.09435

The intersection probability: betting with probability intervals

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2201.01729, Edición 5 January 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2201.01729

Uncertainty measures: The big picture

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2104.06839, Edición 14 April 2021, 2021
Editor: Cornell University
DOI: 10.48550/arxiv.2104.06839

CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks

Autores: Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Publicado en: arXiv preprint arXiv:2401.05043, Edición 2 Feb 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2401.05043

Credal Wrapper of Model Averaging for Uncertainty Estimation on Out-Of-Distribution Detection

Autores: K. Wang, F. Cuzzolin, K. Shariatmadar, D. Moens, H. Hallez
Publicado en: arXiv preprint arXiv:2405.15047, Edición 23 May 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2405.15047

Path Planning Problem under non-probabilistic Uncertainty

Autores: K. Shariatmadar
Publicado en: arXiv preprint arXiv.2212.01388, Edición 1 Dec 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2212.01388

Random-Set Convolutional Neural Network (RS-CNN) for Epistemic Deep Learning

Autores: Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin
Publicado en: arXiv preprint arXiv:2307.05772, Edición 11 Jul 2023, 2023
Editor: Cornell University
DOI: 10.48550/arxiv.2307.05772

E-MCTS: Deep Exploration in Model-Based Reinforcement Learning by Planning with Epistemic Uncertainty

Autores: Oren, Yaniv; Spaan, Matthijs T. J.; Böhmer, Wendelin
Publicado en: arXiv preprint arxiv.2210.13455, Edición 30 Aug 2023, 2023
Editor: Cornell University
DOI: 10.48550/arxiv.2210.13455

Vision in adverse weather: Augmentation using CycleGANs with various object detectors for robust perception in autonomous racing

Autores: Izzeddin Teeti, Valentina Musat, Salman Khan, Alexander Rast, Fabio Cuzzolin, Andrew Bradley
Publicado en: arXiv preprint arxiv.2201.03246, Edición 11 January 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2201.03246

Generalisation of Total Uncertainty in AI: A Theoretical Study

Autores: K. Shariatmadar
Publicado en: arXiv preprint arXiv.2408.00946, Edición 1 Aug 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2408.00946

A geometric approach to conditioning belief functions

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2104.10651, Edición 21 April 2021, 2021
Editor: Cornell University
DOI: 10.48550/arxiv.2104.10651

Conference proceedings (18)

On the Estimation of Image-Matching Uncertainty in Visual Place Recognition

Autores: Mubariz Zaffar, Liangliang Nan, Julian F. P. Kooij
Publicado en: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Edición 31, 2024, Página(s) 17743-17753
Editor: IEEE
DOI: 10.1109/cvpr52733.2024.01680

Bayesian Deep Q-Learning via Sequential Monte Carlo

Autores: Pascal Van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith
Publicado en: 16th European Workshop on Reinforcement Learning (EWRL 2023), Edición 14 Sep 2023, 2023
Editor: EWRL
DOI: 10.5281/zenodo.14245136

Bayesian Model-Free Deep Reinforcement Learning

Autores: Pascal van der Vaart
Publicado en: AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, Edición 6 May 2024, 2024, Página(s) 2782-2784
Editor: IFAAMAS
DOI: 10.5555/3635637.3663285

A Hybrid Graph Network for Complex Activity Detection in Video

Autores: Salman Khan, Izzeddin Teeti, Andrew Bradley, Mohamed Elhoseiny, Fabio Cuzzolin
Publicado en: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Edición 32, 2024, Página(s) 6748-6758
Editor: IEEE
DOI: 10.1109/wacv57701.2024.00662

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autores: Zanger, Moritz A.; Böhmer, Wendelin; Spaan, Matthijs T. J.
Publicado en: 16th European Workshop on Reinforcement Learning (EWRL 2023), Edición 14 Sep 2023, 2023
Editor: EWRL
DOI: 10.48550/arxiv.2306.07124

Bayesian Ensembles for Exploration in Deep Q-Learning

Autores: Pascal Van der Vaart, Neil Yorke-Smith, Matthijs T. J. Spaan
Publicado en: Sixteenth Workshop on Adaptive and Learning Agents (ALA 2024), Edición 6 May 2024, 2024, Página(s) 2528 - 2530
Editor: Adaptive Learning Agents Workshop 2024
DOI: 10.5555/3635637.3663216

Interval Reduced Order Surrogate Modelling Framework for Uncertainty Quantification

Autores: Ghifari A. Faza, Keivan Shariatmadar, Hans Hallez, David Moens
Publicado en: AIAA SCITECH 2024 Forum, Edición 4 Jan 2024, 2024
Editor: American Institute of Aeronautics and Astronautics
DOI: 10.2514/6.2024-0387

A generalisation of the Bellman Equation in Epistemic Reinforcement Learning

Autores: K. Shariatmadar, J. Golub, A. Faza, D. Moens
Publicado en: XAI workshop, Edición May 23 2024, 2024
Editor: Eindhoven Artificial Intelligence Systems Institute
DOI: 10.5281/zenodo.14217032

Epistemic Deep Learning

Autores: Shireen Kudukkil Manchingal, Fabio Cuzzolin
Publicado en: ICML 2022 Workshop on Distribution-Free Uncertainty Quantification, Edición 23 Jul 2022, 2022
Editor: ICML
DOI: 10.48550/arxiv.2206.07609

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autores: Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
Publicado en: The Twelfth International Conference on Learning Representations (ICLR 2024), Edición 7 May 2024, 2024
Editor: ICLR
DOI: 10.5281/zenodo.14236990

Credal Deep Ensembles for Uncertainty Quantification

Autores: K. Wang, K. Shariatmadar, S. Manchingal, F. Cuzzolin, D. Moens and H. Hallez
Publicado en: Thirty-eighth Annual Conference on Neural Information Processing Systems, Edición Dec 9 2024, 2024
Editor: NeurIPS Foundation
DOI: 10.5281/zenodo.14217205

Optimization Under Epistemic Uncertainty With a Focus on Decision-Focused Learning

Autores: Noah Schutte
Publicado en: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Edición 3-9 Aug 2024, 2024, Página(s) 8504-8505
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/967

Science of AI - Total Uncertainty in AI

Autores: Keivan Shariatmadar
Publicado en: Leuven.AI Workshop, Edición Jun 3 2024, 2024
Editor: KU Leuven
DOI: 10.5281/zenodo.14223938

Robust Losses for Decision-Focused Learning

Autores: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Publicado en: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Edición 3-9 Aug 2024, 2024, Página(s) 4868-4875
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/538

YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles

Autores: Aduen Benjumea, Izzeddin Teeti, Fabio Cuzzolin, Andrew Bradley
Publicado en: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Edición 23 December 2021, 2021
Editor: IEEE
DOI: 10.48550/arxiv.2112.11798

Credal learning theory

Autores: Michele Caprio, Maryam Sultana, Eleni Elia and Fabio Cuzzolin
Publicado en: Thirty-eighth Annual Conference on Neural Information Processing Systems, Edición Dec 9 2024, 2024
Editor: NeurIPS Foundation
DOI: 10.5281/zenodo.14216819

Multi-weather city: Adverse weather stacking for autonomous driving

Autores: Valentina Mușat, Ivan Fursa, Paul Newman, Fabio Cuzzolin, Andrew Bradley
Publicado en: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Edición 11-17 Oct 2021, 2022
Editor: IEEE
DOI: 10.1109/iccvw54120.2021.00325

ROAD-R: The Autonomous Driving Dataset with Logical Requirements

Autores: E. Giunchiglia, M. Stoian, S. Khan, F. Cuzzolin and T. Lukasiewicz
Publicado en: IJCAI 2022 - Workshop on Artificial Intelligence for Autonomous Driving (AI4AD 2022), Edición 23 Jul 2022, 2022
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.48550/arxiv.2210.01597

Monographic books (1)

Epistemic Uncertainty in Artificial Intelligence

Autores: Fabio Cuzzolin, Maryam Sultana
Publicado en: Lecture Notes in Computer Science, Edición 23 Apr 2024, 2024, ISBN 978-3-031-57963-9
Editor: Springer Nature
DOI: 10.1007/978-3-031-57963-9

Thesis and dissertations (1)

Uncertainty in Reinforcement Learning and its Application to Scheduling Problems in Manufacturing

Autores: J. Golub, A. Faza, K. Shariatmadar, D. Moens
Publicado en: MSc dissertation, 2024
Editor: KU Leuven
DOI: 10.5281/zenodo.14223900

Book chapters (1)

Improving Metaheuristic Efficiency for Stochastic Optimization by Sequential Predictive Sampling

Autores: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Publicado en: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Edición 25 May 2024, 2024, Página(s) 158-175
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60599-4_10