Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Petra Vidnerová"'
Autor:
Petra Vidnerová, Roman Neruda
Publikováno v:
Neural Information Processing ISBN: 9783030638351
ICONIP (3)
ICONIP (3)
In this paper, we propose a multi-objective evolutionary algorithm for automatic deep neural architecture search. The algorithm optimizes the performance of the model together with the number of network parameters. This allows exploring architectures
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d9528e0cb0daead0a5a4fc08552e512
https://doi.org/10.1007/978-3-030-63836-8_23
https://doi.org/10.1007/978-3-030-63836-8_23
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 127
This paper deals with the vulnerability of machine learning models to adversarial examples and its implication for robustness and generalization properties. We propose an evolutionary algorithm that can generate adversarial examples for any machine l
Publikováno v:
Neural Networks. 23:560-567
A comparison of behavior-based and planning approaches of robot control is presented in this paper. We focus on miniature mobile robotic agents with limited sensory abilities. Two reactive control mechanisms for an agent are considered-a radial basis
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Advances in Neural Networks-ISNN 2010 ISBN: 9783642132773
ISNN (1)
ISNN (1)
In this work we propose two hybrid algorithms combining evolutionary search with optimization algorithms One algorithm memetically combines global evolution with gradient descent local search, while the other is a two-step procedure combining linear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5fd6aad83e846753c09fabd1ba5c5c6
https://doi.org/10.1007/978-3-642-13278-0_68
https://doi.org/10.1007/978-3-642-13278-0_68
Publikováno v:
2008 Second International Conference on Future Generation Communication and Networking Symposia.
A performance of two learning mechanisms for small mobile robots is performed in this paper. Relational reinforcement learning, and radial basis function neural network learned by evolutionary algorithm are trained to perform the same maze exploratio
Publikováno v:
ICARCV
An emergence of intelligent behaviour within a simple robotic agent is studied in this paper. The radial basis function neural network is used as the control mechanism of the robot. Evolutionary algorithm is used to train the agent to perform several
Publikováno v:
Artificial Neural Networks-ICANN 2008 ISBN: 9783540875352
ICANN (1)
ICANN (1)
An emergence of intelligent behavior within a simple robotic agent is studied in this paper. Two control mechanisms for an agent are considered -- a radial basis function neural network trained by evolutionary algorithm, and a traditional reinforceme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77255b76d98b2025c7c8dc73a25961b7
https://doi.org/10.1007/978-3-540-87536-9_74
https://doi.org/10.1007/978-3-540-87536-9_74
Publikováno v:
Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence ISBN: 9783540859833
ICIC (2)
ICIC (2)
We study behavioural patterns learned by a robotic agent by means of two different control and adaptive approaches -- a radial basis function neural network trained by evolutionary algorithm, and a traditional reinforcement Q-learning algorithm. In b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee87fe674b71c5862f453d4d628deda0
https://doi.org/10.1007/978-3-540-85984-0_35
https://doi.org/10.1007/978-3-540-85984-0_35