Projektbeschreibung
Schulung von Fachkräften der Robotik
Im Mittelpunkt des Projekts TRAIL steht ein neuartiges, hochgradig interdisziplinäres und branchenübergreifendes Forschungs- und Ausbildungsprogramm für ein besseres Verständnis von Transparenz im Bereich des Deep Learning, der künstlichen Intelligenz und der Robotiksysteme. Um eine neue Generation von Promotionskandidierenden zu Fachkräften für den Entwurf und die Implementierung von transparenten, interpretierbaren neuronalen Systemen und Robotern auszubilden, wurde ein hochgradig interdisziplinäres Konsortium gebildet, das sich aus Sachverständigen zusammensetzt, die über langjährige Erfahrung auf dem Gebiet der modernen künstlichen Intelligenz und Robotik verfügen, einschließlich tiefer neuronaler Netze, Informatik, Mathematik, sozialer Robotik, Mensch-Roboter-Interaktion und Psychologie. Um transparente Robotersysteme zu bauen, werden diese neuen Promotionskandidierenden die Theorie und Praxis der Prinzipien des internen Entscheidungsverstehens und des externen transparenten Verhaltens kennenlernen.
Ziel
TRAIL strategically focuses on a novel, highly interdisciplinary and cross-sectorial research and training programme for a better understanding of transparency in deep learning, artificial intelligence and robotics systems. In order to train a new generation of Doctoral Candidates to become experts in the design and implementation of transparent, interpretable neural systems and robots, we have built a highly interdisciplinary consortium, containing expert partners with long-standing expertise in cutting-edge artificial intelligence and robotics, including deep neural networks, computer science, mathematics, social robotics, human-robot interaction and psychology. In order to build transparent robotic systems, these new ESR researchers need to learn about the theory and practice of the principles of (1) internal decision understanding and (2) external transparent behaviour. Since the ability to interpret complex robotic systems needs highly interdisciplinary knowledge, we will start, on the decision level, to interpret deep neural learning and analyse what knowledge can be efficiently extracted. At the same time, on the behaviour level, the disciplines of human-robot interaction and psychology will be key in order to understand how to present the extracted knowledge as behaviour in an intuitive and natural way to a human user to integrate the robot into a cooperative human-robot interaction. A scaffolded training curriculum will guarantee that the ESRs have not only a deep understanding of both research areas, but experience optimal skill training to be fully prepared for a successful research career in academia and industry. The importance and need of this research for the industry is clearly visible with the full commitment of 7 leading European and world-wide-operating robotics companies that together cover the majority of Europe’s robot market and a broad spectrum of AI applications.
Wissenschaftliches Gebiet
- social sciencespsychology
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- natural sciencesmathematics
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Schlüsselbegriffe
Programm/Programme
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenFinanzierungsplan
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral NetworksKoordinator
20148 Hamburg
Deutschland