Results 51 to 60 of about 2,128 (206)
Intelligent Prediction of Ship Maneuvering [PDF]
TransNav, 2016 In this paper the author presents an idea of the intelligent ship maneuvering prediction system with the usage of neuroevolution. This may be also be seen as the ship handling system that simulates a learning process of an autonomous control unit ...
Miroslaw Lacki
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Visualizing Neuroevolution in Neural Network Learning
, 2023 This thesis examines options for neural network learning achieved by means of neuroevolution, examines general functioning of neuroevolution, design and implementation of neuroevolution and marginally deals with design and implementation of feed-forward ...
Bednář, Martin
core +1 more source
Predictable Internal Brain Dynamics in EEG and Its Relation to Conscious States
Frontiers in Neurorobotics, 2014 Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature.
Jaewook eYoo +2 more
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Indirect Encoding in Neuroevolutionary Ship Handling [PDF]
TransNav, 2018 In this paper the author compares the efficiency of two encoding schemes for artificial intelligence methods used in the neuroevolutionary ship maneuvering system.
Miroslaw Lacki
doaj +1 more source
Robust optimization through neuroevolution
PLOS ONE, 2019 We propose a method for evolving solutions that are robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediately, without the need to adapt to variations). The obtained results show how the method proposed is effective and computational tractable. It permits to improve performance on
Pagliuca P, Nolfi S
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Neuroevolution with Analog Genetic Encoding [PDF]
, 2006 The evolution of artificial neural networks (ANNs) is often used to tackle difficult control problems. There are different approaches to the encoding of neural networks in artificial genomes. Analog Genetic Encoding (AGE) is a new implicit method derived from the observation of biological genetic regulatory networks.
Dürr, Peter +2 more
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Neuroevolution-Based Efficient Field Effect Transistor Compact Device Models
IEEE Access, 2021 Artificial neural networks (ANN) and multilayer perceptrons (MLP) have proved to be efficient in terms of designing highly accurate semiconductor device compact models (CM).
Ya-Wen Ho +6 more
doaj +1 more source
Neuroevolution-based Inverse Reinforcement Learning [PDF]
2017 IEEE Congress on Evolutionary Computation (CEC), 2017 The problem of Learning from Demonstration is targeted at learning to perform tasks based on observed examples. One approach to Learning from Demonstration is Inverse Reinforcement Learning, in which actions are observed to infer rewards. This work combines a feature based state evaluation approach to Inverse Reinforcement Learning with neuroevolution,
Karan K. Budhraja, Tim Oates 0001
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Modularity Based Linkage Model For Neuroevolution
Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023 Crossover between neural networks is considered disruptive due to the strong functional dependency between connection weights. We propose a modularity-based linkage model at the weight level to preserve functionally dependent communities (building blocks) in neural networks during mixing. A proximity matrix is built by estimating the dependency between
Yukai Qiao, Marcus Gallagher
openaire +5 more sources
Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source