Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Diggelen, J. van"'
Publikováno v:
Harris, D.Li, W.C., 17th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020; Copenhagen; Denmark; 19 July 2020 through 24 July 2020, 12187, 203-220
Artificially intelligent agents will deal with more morally sensitive situations as the field of AI progresses. Research efforts are made to regulate, design and build Artificial Moral Agents (AMAs) capable of making moral decisions. This research is
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http://resolver.tudelft.nl/uuid:45af6586-9d36-42cf-ac42-2580df3ee245
http://resolver.tudelft.nl/uuid:45af6586-9d36-42cf-ac42-2580df3ee245
Autor:
Peeters, M.M.M., Diggelen, J. van, Bosch, K. van den, Bronkhorst, A., Neerincx, M.A., Schraagen, J.M., Raaijmakers, S.
Publikováno v:
AI and Society, 25 June
Within current debates about the future impact of Artificial Intelligence (AI) on human society, roughly three different perspectives can be recognised: (1) the technology-centric perspective, claiming that AI will soon outperform humankind in all ar
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http://resolver.tudelft.nl/uuid:6fc8539f-5585-4a5e-ada1-f5a0688acd34
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Publikováno v:
De La Prieta, F., 18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020; L’Aquila; Italy; 7 October 2020 through 9 October 2020, 1233, 238-249
Artificially intelligent agents increasingly collaborate with humans in human-agent teams. Timely proactive sharing of relevant information within the team contributes to the overall team performance. This paper presents a machine learning approach t
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http://resolver.tudelft.nl/uuid:5cd890c9-bdf2-4442-86f4-6225cdf14983
http://resolver.tudelft.nl/uuid:5cd890c9-bdf2-4442-86f4-6225cdf14983
Autor:
Meyer-Vitali, A.P., Bakker, R.M., Bekkum, M.A. van, Boer, M. de, Burghouts, G., Diggelen, J. van, Dijk, J., Grappiolo, C., Greeff, J. de, Huizing, A., Raaijmakers, S.
Hybrid Artificial Intelligence combines the best of two worlds: the power of recent advances in deep learning with the possibility to explicitly model human knowledge in connected systems. Together, this new generation of AI becomes more controllable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::555390e78e06245c18fe97169a4994f1
http://resolver.tudelft.nl/uuid:510e0747-30f4-4af4-9447-9330b7bd4b47
http://resolver.tudelft.nl/uuid:510e0747-30f4-4af4-9447-9330b7bd4b47
Publikováno v:
IEEE Intelligent Systems, 2, 34, 15-24
Human-agent teams exhibit emergent behavior at the team level, as a result of interactions between individuals within the team. This begs the question how to design artificial team members (agents) as adequate team players that contribute to the team
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http://resolver.tudelft.nl/uuid:e493ef05-23d3-48e1-bf5e-e91630a645d6
Autor:
Beckers, A.L.D., Sijs, J., Diggelen, J. van, Roelof J.E. van Dijk, Bouma, H., Lomme, M., Hommes, R.M., Hillerström, F.H.J., Waa, J.S. van der, Velsen, A.L. van, Mannucci, T., Voogd, J.M., Staal, W. van, Veltman, H.J., Wessels, P.W., Huizing, A.
Publikováno v:
SPIE proceedings 11166,(2019)
Intelligent robotic autonomous systems (unmanned aerial/ground/surface/underwater vehicles) are attractive for military application to relieve humans from tedious or dangerous tasks. These systems require awareness of the environment and their own pe
Externí odkaz:
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Publikováno v:
Demazeau, Y.Bo, A.Bajo, J.Fernández-Caballero, A., Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection. PAAMS 2018, 262-274
Human-machine teaming (HMT) is a promising paradigm to approach future situations in which humans and autonomous systems closely collaborate. This paper introduces SAIL, a design method and framework for the development of HMT-concepts. Starting poin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::177f0aa420cf5a7c6ffa4da1d9c86c1e
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Publikováno v:
Legatt, M.Fechtelkotter, P., AHFE 2017 International Conference on Human Factors in Energy : Oil, Gas, Nuclear and Electric Power Industries, 2017. 17 July 2017 through 21 July 2017, 599, 48-59
Fechtelkotter, P.Legatt, M.Series editor:Kacprzyk, J., Proceedings of the AHFE 2017 International Conference on Human Factors in Energy : Oil, Gas, Nuclear and Electric Power Industries, July 17–21, 2017, The Westin Bonaventure Hotel, Los Angeles, California, USA, 48-59
Fechtelkotter, P.Legatt, M.Series editor:Kacprzyk, J., Proceedings of the AHFE 2017 International Conference on Human Factors in Energy : Oil, Gas, Nuclear and Electric Power Industries, July 17–21, 2017, The Westin Bonaventure Hotel, Los Angeles, California, USA, 48-59
This paper proposes a human-centered approach to Dynamic Position-ing systems which combines multiple technologies in an intelligent operator sup-port system (IOSS). IOSS allows the operator to be roaming and do other tasks in quiet conditions. When
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3bdfc297b1ed5d559a2fc669a85285c4
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Publikováno v:
16th International Conference on Practical Applications of Agents, Multi-Agent Systems, PAAMS 2018. 20 June 2018 through 22 June 2018, Demazeau, Y.Bajo, J.Fernandez-Caballero, A.An, B., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10978 LNAI, 361-365
Human-machine teaming (HMT) is a promising paradigm to approach situations in which humans and autonomous systems must closely collaborate. This paper describes SAIL, a software framework for implementing HMT-concepts. The approach of SAIL is to inte
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Publikováno v:
Said, A.Komatsu, T., 2018 Joint ACM IUI Workshops, ACMIUI-WS 2018. 11 March 2018, 2068
Explainable AI becomes increasingly important as the use of intelligent systems becomes more widespread in high-risk domains. In these domains it is important that the user knows to which degree the system’s decisions can be trusted. To facilitate
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https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a121c52f6659acb8dbc5d1441d54fb00
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