Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Mahdi, B A"'
Autor:
Nematollahi, Iman, Rosete-Beas, Erick, Azad, Seyed Mahdi B., Rajan, Raghu, Hutter, Frank, Burgard, Wolfram
For autonomous skill acquisition, robots have to learn about the physical rules governing the 3D world dynamics from their own past experience to predict and reason about plausible future outcomes. To this end, we propose a transformation-based 3D vi
Externí odkaz:
http://arxiv.org/abs/2209.11693
Publikováno v:
In Revue Française d'Allergologie October 2022 62(6):536-539
Publikováno v:
IOP Conference Series: Earth & Environmental Science; Sep2023, Vol. 1252 Issue 1, p1-10, 10p
Autor:
Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard
Publikováno v:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Autor:
Mahdi, B. H.1 Berivan.hadi@uod.ac, Yousif, K. M.2 Kamil.yousif@uoz.edu.krd, Salih Dosky, L. M.3 Luqman.kader@uod.ac
Publikováno v:
Iraqi Journal of Agricultural Sciences. 2020, Vol. 51 Issue 4, p1160-1172. 13p.
Autor:
Mahdi, B., Auda, F. M.
Publikováno v:
Magazine of Al-Kufa University for Biology; 2023, Vol. 15 Issue 2, p19-23, 5p
Publikováno v:
Journal of Communications Software and Systems, Vol 10, Iss 3, Pp 163-178 (2014)
An ever increasing number of interconnected embedded devices, or Machine-to-Machine (M2M) systems, are changing the way we live, work and play. M2M systems as a whole are typically characterized by the diversity in both the type of device and type of
Externí odkaz:
https://doaj.org/article/ec4197dfbf83447a9393a0b204d43ff1
Autor:
Fajar, J. K.1 gembyok@gmail.com, Mahdi, B. A.2, Heriansyah, T.3 teuku_hery@unsyiah.ac.id, Rohman, M. S.4,5
Publikováno v:
Archives of Hellenic Medicine / Arheia Ellenikes Iatrikes. Jul/Aug2019, Vol. 36 Issue 4, p494-502. 9p.
Autor:
Seyed Mahdi B. Azad, Minh Q. Phan
Publikováno v:
The Journal of the Astronautical Sciences. 67:630-656
A design of optimal controllers based on a reinforcement learning method called Q-Learning is presented. Central to Q-Learning is the Q-function which is a function of the state and all input variables. This paper shows that decoupled-in-the-inputs Q
Autor:
Seyed Mahdi B. Azad, Minh Q. Phan
Publikováno v:
Modeling, Simulation and Optimization of Complex Processes HPSC 2018 ISBN: 9783030552398
This paper provides a conceptual framework to design an optimal controller for a bilinear system by reinforcement learning. Model Predictive Q-Learning (MPQ-L) combines Model Predictive Control (MPC) with Q-Learning. MPC finds an initial sub-optimal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::771ca52bce66dd6e99277113782e1ecd
https://doi.org/10.1007/978-3-030-55240-4_5
https://doi.org/10.1007/978-3-030-55240-4_5