Zobrazeno 1 - 10
of 27 228
pro vyhledávání: '"A. A. Hafez"'
Humanoids have the potential to be the ideal embodiment in environments designed for humans. Thanks to the structural similarity to the human body, they benefit from rich sources of demonstration data, e.g., collected via teleoperation, motion captur
Externí odkaz:
http://arxiv.org/abs/2411.01349
Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), specifically in modeling the environment's dynamics using Transformer D
Externí odkaz:
http://arxiv.org/abs/2407.18841
Learning a locomotion controller for a musculoskeletal system is challenging due to over-actuation and high-dimensional action space. While many reinforcement learning methods attempt to address this issue, they often struggle to learn human-like gai
Externí odkaz:
http://arxiv.org/abs/2407.11658
Autor:
Ghaemi, Hafez, Jamshidi, Shirin, Mashreghi, Mohammad, Ahmadabadi, Majid Nili, Kebriaei, Hamed
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been risk-neutral, i.e., agents are assumed to optimize a performance metric
Externí odkaz:
http://arxiv.org/abs/2406.06041
Autor:
Nanwani, Laksh, Gupta, Kumaraditya, Mathur, Aditya, Agrawal, Swayam, Hafez, A. H. Abdul, Krishna, K. Madhava
Publikováno v:
Advanced Robotics - Taylor and Francis - 2024
Humans excel at forming mental maps of their surroundings, equipping them to understand object relationships and navigate based on language queries. Our previous work SI Maps [1] showed that having instance-level information and the semantic understa
Externí odkaz:
http://arxiv.org/abs/2404.17922
Publikováno v:
Egyptian Journal of Biological Pest Control, Vol 28, Iss 1, Pp 1-6 (2018)
Abstract The objective of this study was to apply a biological control program on cucumber crop under greenhouse conditions, using biological control agents compared with insecticides to control the cotton aphid, Aphis gossypii Glover. The treatments
Externí odkaz:
https://doaj.org/article/3f911c532f294530838401b422b51b6b
Autor:
Talukder, Md. Simul Hasan, Akter, Sharmin, Nur, Abdullah Hafez, Aljaidi, Mohammad, Sulaiman, Rejwan Bin, Alkoradees, Ali Fayez
Sugarcane, a key crop for the world's sugar industry, is prone to several diseases that have a substantial negative influence on both its yield and quality. To effectively manage and implement preventative initiatives, diseases must be detected promp
Externí odkaz:
http://arxiv.org/abs/2403.18870
Classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents. However, in settings where agents need to consider or model human economic or social preferences, a notion of risk must be incorporated i
Externí odkaz:
http://arxiv.org/abs/2402.05906
Autor:
Ebekozien, Andrew, Aigbavboa, Clinton, Thwala, Wellington Didibhuku, Samsurijan, Mohamad Shaharudin, Ahmed, Mohamed Ahmed Hafez, Aliu, John, Adekunle, Samuel Adeniyi
Publikováno v:
International Journal of Building Pathology and Adaptation, 2024, Vol. 42, Issue 7, pp. 93-112.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJBPA-04-2024-0070
Autor:
Ebekozien, Andrew, Aigbavboa, Clinton, Samsurijan, Mohamad Shaharudin, Ahmed, Mohamed Ahmed Hafez, Akinradewo, Opeoluwa, Omoh-Paul, Igbebo
Publikováno v:
International Journal of Building Pathology and Adaptation, 2024, Vol. 42, Issue 7, pp. 35-54.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJBPA-01-2024-0003