Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Ayush Raina"'
Publikováno v:
Journal of Mechanical Design. 145
Advances in artificial intelligence (AI) offer new opportunities for human–AI cooperation in engineering design. Human trust in AI is a crucial factor in ensuring an effective human–AI cooperation, and several approaches to enhance human trust in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a18bd16f6254f6c61805dd00a443cad9
https://doi.org/10.1115/1.4056499
https://doi.org/10.1115/1.4056499
Publikováno v:
Journal of Mechanical Design. 145
Building an AI agent that can design on its own has been a goal since the 1980s. Recently, deep learning has shown the ability to learn from large-scale data, enabling significant advances in data-driven design. However, learning over prior data limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd8b23b87f715649b0e16d5a8b30871a
https://doi.org/10.1115/1.4056221
https://doi.org/10.1115/1.4056221
Publikováno v:
Engineering Optimization. 54:2017-2033
Unmanned aerial vehicles (UAVs) have became appreciably compact and lightweight over the years, imposing stricter geometric and stability constraints. The new-generation UAVs are required to carry ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86e256156750501da4dc6831027ec940
https://doi.org/10.1080/0305215x.2021.1971212
https://doi.org/10.1080/0305215x.2021.1971212
Publikováno v:
Journal of Mechanical Design. 145
Decision-making assistance by artificial intelligence (AI) during design is only effective when human designers properly utilize the AI input. However, designers often misjudge the AI’s and/or their own ability, leading to erroneous reliance on AI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::937741e1aa74f3c2ac6c1093d3f0c50e
https://doi.org/10.1115/1.4055123
https://doi.org/10.1115/1.4055123
Publikováno v:
Volume 3B: 48th Design Automation Conference (DAC).
Building an AI agent that can design on its own has been a goal since the 1980s. Recently, deep learning has shown the ability to learn from large-scale data, enabling significant advances in data-driven design. However, learning over prior data limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3081e989b7f791238ce7e6b026f15295
https://doi.org/10.1115/detc2022-89740
https://doi.org/10.1115/detc2022-89740
Publikováno v:
Volume 3B: 48th Design Automation Conference (DAC).
Advances in artificial intelligence (AI) offer new opportunities for human-AI collaboration in engineering design. Human trust in AI is a crucial factor in ensuring an effective human-AI collaboration, and several approaches to enhance human trust in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a58f6f7edb84ae13468e875cc100d0cf
https://doi.org/10.1115/detc2022-88535
https://doi.org/10.1115/detc2022-88535
Publikováno v:
Volume 6: 34th International Conference on Design Theory and Methodology (DTM).
Decision-making assistance by artificial intelligence (AI) during design is only effective when human designers properly utilize AI input. However, designers often misjudge the AI’s and/or their own ability, leading to erroneous reliance on AI and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6422b11a03f23673fc0b509637eb9b15
https://doi.org/10.1115/detc2022-88574
https://doi.org/10.1115/detc2022-88574
Publikováno v:
Proceedings of the Design Society: DESIGN Conference. 1:355-364
Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology pres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7111e15a28b7171df6928eee3cffa1f0
https://doi.org/10.1017/dsd.2020.42
https://doi.org/10.1017/dsd.2020.42
Publikováno v:
Journal of Mechanical Design. 143
Engineering design problems often involve large state and action spaces along with highly sparse rewards. Since an exhaustive search of those spaces is not feasible, humans utilize relevant domain knowledge to condense the search space. Deep learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::301be55d3a34c83ca9649ae89f03ae80
https://doi.org/10.1115/1.4051013
https://doi.org/10.1115/1.4051013
Generative design problems often encompass complex action spaces that may be divergent over time, contain state-dependent constraints, or involve hybrid (discrete and continuous) domains. To address those challenges, this work introduces Design Strat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13726c6c91a8b38d3f14d4fdbded2691
