Results 21 to 30 of about 2,128 (206)
Neuroevolutionary reinforcing learning of neural networks
Системный анализ и прикладная информатика, 2022 The article presents the results of combining 4 different types of neural network learning: evolutionary, reinforcing, deep and extrapolating. The last two are used as the primary method for reducing the dimension of the input signal of the system and ...
Y. A. Bury, D. I. Samal
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IEEE Access, 2021 Neural architecture search has proven to be highly effective in the design of efficient convolutional neural networks that are better suited for mobile deployment than hand-designed networks.
William McNally +3 more
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Neuroevolution Trajectory Networks of the Behaviour Space [PDF]
, 2022 A network-based modelling technique, search trajectory networks (STNs), has recently helped to understand the dynamics of neuroevolution algorithms such as NEAT.
Ochoa, Gabriela +2 more
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Neuroevolution for RTS Micro [PDF]
2018 IEEE Conference on Computational Intelligence and Games (CIG), 2018 This paper uses neuroevolution of augmenting topologies to evolve control tactics for groups of units in real-time strategy games. In such games, players build economies to generate armies composed of multiple types of units with different attack and movement characteristics to combat each other.
Aavaas Gajurel +3 more
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Monarch Butterfly Optimization Based Convolutional Neural Network Design
Mathematics, 2020 Convolutional neural networks have a broad spectrum of practical applications in computer vision. Currently, much of the data come from images, and it is crucial to have an efficient technique for processing these large amounts of data.
Nebojsa Bacanin +4 more
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An Adaptive Island Model of Population for Neuroevolutionary Ship Handling
Polish Maritime Research, 2022 This study presents a method for the dynamic value assignment of evolutionary parameters to accelerate, automate and generalise the neuroevolutionary method of ship handling for different navigational tasks and in different environmental conditions.
Łącki Mirosław
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Neuroevolution-Based Generation of Tests and Oracles for Games
, 2022 Game-like programs have become increasingly popular in many software engineering domains such as mobile apps, web applications, or programming education.
Patric Feldmeier (11360424)
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Guiding Neuroevolution with Structural Objectives [PDF]
Evolutionary Computation, 2020 Abstract The structure and performance of neural networks are intimately connected, and by use of evolutionary algorithms, neural network structures optimally adapted to a given task can be explored. Guiding such neuroevolution with additional objectives related to network structure has been shown to improve performance in some cases ...
Ellefsen, Kai Olav +2 more
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Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022 Evolutionary computation has been shown to be a highly effective method for training neural networks, particularly when employed at scale on CPU clusters. Recent work have also showcased their effectiveness on hardware accelerators, such as GPUs, but so far such demonstrations are tailored for very specific tasks, limiting applicability to other ...
Yujin Tang, Yingtao Tian, David Ha
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Neuroevolution untuk optimalisasi parameter jaringan saraf tiruan [PDF]
, 2023 Artificial Neural Network is a supervised learning method for various classification problems. Artificial Neural Network uses training data to identify patterns in the data; therefore, training phase is crucial.
Purnomo, Hindriyanto Dwi +3 more
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