Deliverables
Report including the final publishable summary report and all the technical activities performed during the whole project It includes an assessment of the project achievements towards the RD initial goals An initial version will be available at M22
This document develops a clear plan of the validation activities that will be conducted within the project for each one of the target domains CDR and ATFM including the scope of the validation approach and methodology relevant criteria to be assessed and humanspecific measures that need to be gathered for the defined scenarios
This document will deliver a merge of contextual requirements from both the operational and technical use cases descriptions, as well as a roadmap of delegation of functionalities between human actors and the machine.
This document will consolidate the transparency requirements derived from the human machine interactions for each level of automation in the ATFM and CDR operational use cases, and that will need to be accomplished during the implementation activities. A first draft will be available at M6 for the ATFM transparency requirements.
This document will consolidate the results of the analysis performed based on the feedback and data gathered during the execution of the ATFM and CDR experiments including objectives achieved further research and recommendations for derivation of transparency criteria A first draft will be available at M14 containing the preliminary results of the ATFM experiment
Document that contains the description of the ATFM and CDR prototype including functionalities and improvements derived from the validation activities conducted A first draft will be available at M11 describing the ATFM prototype
This document constitutes the final identification of the requirements that will ensure that different transparencyexplainability criteria are fulfilled when AIMLbased models are implemented This document will take as input the results from the validation activities conducted along the project and will combine analysis and expertise to specify the requirements A first draft will be available at M14
This document will provide an identification of promising state of the art explainable reinforcement learning methods and deliver a reference of the XAI techniques for detecting problems and prescribing solutions in the ATFM and CDR operational cases A first draft will be available at M12 delivering a reference for the ATFM prototype
Description of the Visualizations and Visual Analytics methods implemented to improve the explainability and understandability of XAI ATFM and CDR Operational Cases A first draft will be available at M12 containing the description of the visualizations and visual analytics methods implemented for the ATFM use case
This deliverable comprises the planning of the dissemination exploitation and communication activities
This document will describe in detail the use cases to be developed under TAPAS project: (a) from the operational point of view; and (b) from the technological perspective, providing also additional requirements and feasibility analysis of the solutions proposed.
This deliverable comprises the results of the implementation of the dissemination exploitation and communication activities according to the Exploitation and Dissemination Plan A first draft will be available at M24
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Publications
Author(s): George Vouros, George Papadopoulos, Alevizos Bastas, Jose Manuel Cordero, Ruben Rodriguez Rodriguez
Published in: Volume 351: PAIS 2022, 2022
Publisher: PAIS (Prestigious Applications of Intelligent Systems)
DOI: 10.48550/arxiv.2206.07403
Author(s): Gennady Andrienko, Natalia Andrienko, Jose Manuel Cordero Garcia, Dirk Hecker, George A. Vouros
Published in: IEEE Computer Graphics and Applications, 02721716, 2022, ISSN 0272-1716
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mcg.2022.3163437
Author(s): Theocharis Kravaris, Konstantinos Lentzos, Georgios Santipantakis, George A. Vouros, Gennady Andrienko, Natalia Andrienko, Ian Crook, Jose Manuel Cordero Garcia & Enrique Iglesias Martinez
Published in: Applied Intelligence, 0924669X, 2022, ISSN 0924-669X
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10489-022-03605-1
Author(s): N. Andrienko, G. Andrienko, L. Adilova and S. Wrobel
Published in: IEEE Computer Graphics and Applications, 02721716, 2022, ISSN 0272-1716
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mcg.2021.3130314
Author(s): George A. Vouros
Published in: ACM Computing Surveys, 03600300, 2022, ISSN 0360-0300
Publisher: Association for Computing Machinary, Inc.
DOI: 10.1145/3527448
Author(s): Theocharis Kravaris and George A. Vouros
Published in: Multi-Agent Technologies and Machine Learning, 2022
Publisher: IntechOpen
DOI: 10.5772/intechopen.105627