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CORDIS - EU research results
CORDIS

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

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Reference Architecture and Specifications v2 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

Reference Architecture and Specifications v1 (opens in new window)

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 (opens in new window)

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

Integrated Pilot Systems and Pilot Operations v1 (opens in new window)

Prototype implementation and demonstrators of all pilots/UCs

Training Centre Development for Human-AI collaboration v1 (opens in new window)

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

Requirements Analysis, Reference Scenarios, Applicable Standards and Regulations v1 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

Next Level Human Machine Interfaces 1st version available v1 (opens in new window)

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 (opens in new window)

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 (opens in new window)

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

Publications

Predicting Defect Rates of Printed Circuit Board Assemblies: Towards Zero Defect Manufacturing and Zero-Maintenance Strategies (opens in new window)

Author(s): E. Miedema, H. Kortman, C. Emmanouilidis
Published in: IFAC-PapersOnLine, Issue 58, 2024, ISSN 2405-8963
Publisher: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.08.056

Neural Computing and Applications (opens in new window)

Author(s): George Fatouros; Kostas Metaxas; John Soldatos; Dimosthenis Kyriazis
Published in: Neural Computing and Applications, 2024, ISSN 0941-0643
Publisher: Springer Verlag
DOI: 10.1007/S00521-024-10613-4

A Dynamic Multi-objective Scheduling Approach for Gradient-Based Reinforcement Learning (opens in new window)

Author(s): Katharina Hengel, Achim Wagner, Martin Ruskowski
Published in: IFAC-PapersOnLine, Issue 58, 2024, ISSN 2405-8963
Publisher: Elsevier BV
DOI: 10.1016/J.IFACOL.2024.09.087

Towards using behavior trees in industrial automation controllers (opens in new window)

Author(s): Aleksandr Sidorenko, Mahdi Rezapour, Achim Wagner, Martin Ruskowski
Published in: Editorial 57th CIRP International Conference on Manufacturing Systems (CIRP CMS 2024), Elsevier, 2024, ISSN 2212-8271
Publisher: 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 (opens in new window)

Author(s): Christos Emmanouilidis, Ype Wijnia
Published in: IFAC-PapersOnLine, Issue 58, 2024, ISSN 2405-8963
Publisher: 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 (opens in new window)

Author(s): Georgios Fatouros, Konstantinos Metaxas, John Soldatos, Dimosthenis Kyriazis
Published in: SSRN Electronic Journal, 2024, ISSN 1556-5068
Publisher: Elsevier BV
DOI: 10.2139/ssrn.4693849

Integrating Knowledge Graphs and Large Language Models for Querying in an Industrial Environment (opens in new window)

Published in: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Publisher: Jožef Stefan Instutute
DOI: 10.70314/is.2024.sikdd.5

Skills Composition Framework for Reconfigurable Cyber-Physical Production Modules (opens in new window)

Author(s): Aleksandr Sidorenko, Achim Wagner, Martin Ruskowski
Published in: """2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA) IEEE Industrial Electronics Magazine""", 2024
Publisher: IEEE
DOI: 10.1109/ETFA61755.2024.10710864

Facilitating AI and System Operator Synergy: Active Learning-Enhanced Digital Twin Architecture for Day-Ahead Load Forecasting (opens in new window)

Author(s): Costas Mylonas, Titos Georgoulakis, Magda Foti
Published in: 2024 International Conference on Smart Energy Systems and Technologies (SEST), 2024
Publisher: IEEE
DOI: 10.1109/SEST61601.2024.10693980

Enhancing Ontology Engineering with LLMs: From Search to Active Learning Extensions (opens in new window)

Published in: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Publisher: Jožef Stefan Instutute
DOI: 10.70314/is.2024.sikdd.28

Integrating Knowledge Graphs and Large Language Models for Querying in an Industrial Environment (opens in new window)

Author(s): Hočevar, Domen and Klemen Kenda
Published in: 2024
Publisher: 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 (opens in new window)

Published in: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Publisher: Jožef Stefan Instutute
DOI: 10.70314/IS.2024.SIKDD.28

Enhancing Ontology Engineering with LLMs: From Search to Active Learning Extensions (opens in new window)

Author(s): Kholmska, Ganna, Klemen Kenda and Jože Rožanec
Published in: Proceedings of Data Mining and Data Warehauses – Sikdd 2024, 2024
Publisher: Jožef Stefan Instutute
DOI: 10.70314/IS.2024.SIKDD.28

Integrating Knowledge and Data-Driven Artificial Intelligence for Decisional Enterprise Interoperability (opens in new window)

Author(s): Christos Emmanouilidis, Sabine Waschull, Jessica Zotelli
Published in: Communications in Computer and Information Science, Innovative Intelligent Industrial Production and Logistics, 2025
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-80775-6_26

Robust Novel Defect Detection with Neurosymbolic AI (opens in new window)

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

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