Hybrid Human-AI Decision Support for Enhanced Human Empowerment in Dynamic Situations

Informations projet

HumAIne

N° de convention de subvention: 101120218

DOI

10.3030/101120218

Date de signature de la CE 11 Septembre 2023

Date de début 1 Octobre 2023

Date de fin 30 Septembre 2026

Financé au titre de

• Digital, Industry and Space

Coût total

€ 7 658 375,00

Contribution de l’UE

€ 7 658 375,00

Coordonné par

GFT ITALIA SRL
Italy

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (14)

Reference Architecture and Specifications v2

Documentation of the HumAIne RA (T2.6) and technical specifications. Including task and workflow modelling (T2.2) and semantic knowledge modelling (T2.3).

XAI methods and Benchmark Suite for Human-AI systems v1

Delivers the software implementations of (i) Glass-box models (T3.1), (ii) Black-box models’ interpretability (T3.2), and (iii) Benchmark Suite (T3.5).

HumAIne Platform Integration v1

Reports periodically on HumAIne platform overall implementation (T5.1, T5.2, T5.3)

Reference Architecture and Specifications v1

Documentation of the HumAIne RA (T2.6) and technical specifications. Including task and workflow modelling (T2.2) and semantic knowledge modelling (T2.3).

Use Cases Specification and Pilot Sites Preparation v1

Report on the detailed specifications of the pilots & UCs (T6.1)

Integrated Pilot Systems and Pilot Operations v1

Prototype implementation and demonstrators of all pilots/UCs

Training Centre Development for Human-AI collaboration v1

Delivers the development related to the Digital Training Center (T5.4)

Requirements Analysis, Reference Scenarios, Applicable Standards and Regulations v1

Report on the analysis of requirements, the review of the state of the art and the reference scenarios for human-AI based on T2.1. It includes analysis of the applicable standards, including information about their impact on the projects developments (T2.4).

Advanced AI Platforms for human-AI collaboration v1

Delivers the software implementations of (i) Active Learning Platform and models (T4.2), (ii) Swarm Intelligence Platform and models (T4.3), (iii) Neuro-Symbolic AI Platform and models (T4.4). It also analyses the data supported and used by the AI platforms (T4.1) and platforms’ adaptation to different requirements (T4.5).

Dissemination, Communication, and Standardization Activities v1

A report (living document) on the outcomes of T7.1, T7.2, T7.5 that will be delivered periodically. It also presents the projects training activities (T7.4).

Dissemination and Community Building Plan

Report on planning of T7.1 and T7.2.

Next Level Human Machine Interfaces 1st version available v1

Delivers the implementations of (i) Human Machine Interfaces (T3.3), (ii) Knowledge Exchange Techniques (T3.4)

Requirements Analysis, Reference Scenarios, Applicable Standards and Regulations v2

Report on the analysis of requirements, the review of the state of the art and the reference scenarios for human-AI based on T2.1. It includes analysis of the applicable standards, including information about their impact on the projects developments (T2.4).

Detailed Methodology for User Studies and Co-Creation v1

Detailed methodology for user studies and cocreation activities. (T2.6)

Data Management Plan (1)

Data Management Plan v1

The projects DMP in two versions;

Publications

Peer reviewed articles (6)

Predicting Defect Rates of Printed Circuit Board Assemblies: Towards Zero Defect Manufacturing and Zero-Maintenance Strategies

Auteurs: E. Miedema, H. Kortman, C. Emmanouilidis
Publié dans: IFAC-PapersOnLine, Numéro 58, 2024, ISSN 2405-8963
Éditeur: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.08.056

Neural Computing and Applications

Auteurs: George Fatouros; Kostas Metaxas; John Soldatos; Dimosthenis Kyriazis
Publié dans: Neural Computing and Applications, 2024, ISSN 0941-0643
Éditeur: Springer Verlag
DOI: 10.1007/S00521-024-10613-4

A Dynamic Multi-objective Scheduling Approach for Gradient-Based Reinforcement Learning

Auteurs: Katharina Hengel, Achim Wagner, Martin Ruskowski
Publié dans: IFAC-PapersOnLine, Numéro 58, 2024, ISSN 2405-8963
Éditeur: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.09.087

Towards using behavior trees in industrial automation controllers

Auteurs: Aleksandr Sidorenko, Mahdi Rezapour, Achim Wagner, Martin Ruskowski
Publié dans: Editorial 57th CIRP International Conference on Manufacturing Systems (CIRP CMS 2024), Elsevier, 2024, ISSN 2212-8271
Éditeur: Elsevier, Science Direct, Procedia CIRP
DOI: 10.1016/J.PROCIR.2024.10.233

Asset criticality and risk prediction via machine learning in wind farms: problem-based educational activities in a smart industry operations course

Auteurs: Christos Emmanouilidis, Ype Wijnia
Publié dans: IFAC-PapersOnLine, Numéro 58, 2024, ISSN 2405-8963
Éditeur: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.08.119

Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Auteurs: Georgios Fatouros, Konstantinos Metaxas, John Soldatos, Dimosthenis Kyriazis
Publié dans: SSRN Electronic Journal, 2024, ISSN 1556-5068
Éditeur: Elsevier BV
DOI: 10.2139/ssrn.4693849

Conference proceedings (7)

Integrating Knowledge Graphs and Large Language Models for Querying in an Industrial Environment

Publié dans: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Éditeur: Jožef Stefan Instutute
DOI: 10.70314/is.2024.sikdd.5

Skills Composition Framework for Reconfigurable Cyber-Physical Production Modules

Auteurs: Aleksandr Sidorenko, Achim Wagner, Martin Ruskowski
Publié dans: """2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA) IEEE Industrial Electronics Magazine""", 2024
Éditeur: IEEE
DOI: 10.1109/ETFA61755.2024.10710864

Facilitating AI and System Operator Synergy: Active Learning-Enhanced Digital Twin Architecture for Day-Ahead Load Forecasting

Auteurs: Costas Mylonas, Titos Georgoulakis, Magda Foti
Publié dans: 2024 International Conference on Smart Energy Systems and Technologies (SEST), 2024
Éditeur: IEEE
DOI: 10.1109/SEST61601.2024.10693980

Enhancing Ontology Engineering with LLMs: From Search to Active Learning Extensions

Publié dans: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Éditeur: Jožef Stefan Instutute
DOI: 10.70314/is.2024.sikdd.28

Integrating Knowledge Graphs and Large Language Models for Querying in an Industrial Environment

Auteurs: Hočevar, Domen and Klemen Kenda
Publié dans: 2024
Éditeur: Proceedings of Data Mining and Data Warehauses – Sikdd 2024
DOI: 10.70314/IS.2024.SIKDD.5

Enhancing Ontology Engineering with LLMs: From Search to Active Learning Extensions

Publié dans: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Éditeur: Jožef Stefan Instutute
DOI: 10.70314/IS.2024.SIKDD.28

Enhancing Ontology Engineering with LLMs: From Search to Active Learning Extensions

Auteurs: Kholmska, Ganna, Klemen Kenda and Jože Rožanec
Publié dans: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Éditeur: Jožef Stefan Instutute
DOI: 10.70314/IS.2024.SIKDD.28

Book chapters (2)

Integrating Knowledge and Data-Driven Artificial Intelligence for Decisional Enterprise Interoperability

Auteurs: Christos Emmanouilidis, Sabine Waschull, Jessica Zotelli
Publié dans: Communications in Computer and Information Science, Innovative Intelligent Industrial Production and Logistics, 2025
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-80775-6_26

Robust Novel Defect Detection with Neurosymbolic AI

Auteurs: Spyros Theodoropoulos, Georgios Makridis, Dimosthenis Kyriazis, Panayiotis Tsanakas
Publié dans: IFIP Advances in Information and Communication Technology, Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments, 2024
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-71637-9_26