Deliverables Documents, reports (10) Management Report This deliverable concerns a status report on the technical achievements of TRUST in the first nine months of the projects A brief description of the development of each task will be provided including documentation of procedures screenshots preliminary results and identified risks Data management plan V2 Saliency measures for identifying causally variables of explanations This report will present the saliency measures and code for identifying causally relevant variables of humanlike explanations The relevant variables are those to be considered during the discovery and communication of causal explanations These variables will be formalised and measurable in terms of their specificity insensitivity proximity and other characteristics known to be preferred by humans User studies on the realization of explanations The deliverable reports the result of the qualitative studies on the best way to present explanation content produced in WP3 and provides recommendations for Task 22 Framework requirements document This deliverable will describe the functional and nonfunctional requirements of the framework as well as the interactions and dependencies between the building blocks The use case needs will also be detailed and reported in this document ensuring that the framework is adequate to different problems and sectors Communication & Dissemination plan This report will present the Communication Dissemination Plan of TRUST where the strategy to raise public awareness about the project outcomes will be detailed and scheduled In addition to academic publications and conferences the plan includes events promotion participation in working groups and online forums and educational content creation such as courseware and webinars The plan will include KPIs and their target values as well as the Partner responsible for each communicationdissemination method Evaluation with healthcare experts of learned models This deliverable concerns a formal validation of the AI models developed for the first simplified version of the healthcare problem These models will be designed by NWOI and validated by medical experts from LUMC The report will present the first insights on the models results and suggestions for modifications Initial validation of the explainable AI models from business experts This deliverable concerns a formal validation of the AI models developed for the first simplified version of the online retail problem These models will be designed by LTP and validated by practitioners from Sonae INESC will coordinate the development and validation process Data management plan This deliverable presents the Data Management Plan of TRUSTAI detailing the types of data generatedcollected how it will be exploited protected and the standards to be considered Initial validation of the explainable AI models from energy experts This deliverable concerns a formal validation of the AI models developed for the first simplified version of the energy problem These models will be designed by POLIS21 and validated by practitioners from the industry Publications Peer reviewed articles (5) Open data or open access? The case of building data. Author(s): Sakkas, N., Yfanti, S Published in: Academia Letters, 2021, ISSN 2771-9359 Publisher: Academia.edu DOI: 10.20935/al3629 Deep neural networks using a single neuron: folded-in-time architecture using feedback-modulated delay loops Author(s): Stelzer, Florian; Röhm, André; Vicente, Raul; Fischer, Ingo; Yanchuk, Serhiy Published in: Nature Communications, Issue 20411723, 2021, ISSN 2041-1723 Publisher: Nature Publishing Group DOI: 10.48550/arxiv.2011.10115 Quantifying Reinforcement-Learning Agent’s Autonomy, Reliance on Memory and Internalisation of the Environment Author(s): Anti Ingel, Abdullah Makkeh, Oriol Corcoll and Raul Vicente Published in: Entropy, Issue 10994300, 2022, ISSN 1099-4300 Publisher: Multidisciplinary Digital Publishing Institute (MDPI) DOI: 10.3390/e24030401 Interpretable Forecasting of Energy Demand in the Residential Sector Author(s): Nikos Sakkas; Sofia Yfanti; Costas Daskalakis; Eduard Barbu; Marharyta Domnich Published in: Issue 20, Issue 19961073, 2021, ISSN 1996-1073 Publisher: Multidisciplinary Digital Publishing Institute (MDPI) DOI: 10.3390/en14206568 Drivers of and counterfactuals for the final energy and electricity consumption in EU industry Author(s): Sakkas, N., Athanasiou, N. Published in: Academia Letters, Issue 27719359, 2021, ISSN 2771-9359 Publisher: Academia.edu DOI: 10.20935/al3451 Conference proceedings (5) Building data models and data sharing. Purpose, approaches and a case study on explainable demand response Author(s): Nikos Sakkas, Ch. Chaniotaki, Nikitas. Sakkas, Costas Daskalakis Published in: Emerging Concepts for Sustainable Built Environment, 2022 Publisher: SBEfin 2022 Conference Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models Author(s): Sijben, Evi; Alderliesten, Tanja; Bosman, Peter Published in: GECCO '22: Genetic and Evolutionary Computation Conference, 2022, ISBN 978-1-4503-9237-2 Publisher: Association for Computing Machinery, New York, NY, United States DOI: 10.48550/arxiv.2203.13347 Explanatory World Models via Look Ahead Attention for Credit Assignment Author(s): Oriol Corcoll and Raul Vicente Published in: Issue 26403498, 2022, ISSN 2640-3498 Publisher: Proceedings of Machine Learning Research Real time Data and Application Sharing and Collaboration for the Building Energy Domain Author(s): N. Sakkas, M. Papadopoulou, D. Sakkas Published in: 2021 Publisher: World of Digital Built Environment WDBE 2021 Evolvability degeneration in multi-objective genetic programming for symbolic regression Author(s): Dazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman Published in: GECCO '22: Genetic and Evolutionary Computation Conference, 2022 Publisher: Association for Computing Machinery, New York, NY, United States DOI: 10.1145/3512290.3528787 Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
