Artificial life based on boids model and evolutionary chaotic neural networks for creating artworks

Choi, Tae Jong; Ahn, Chang Wook

doi:10.1016/j.swevo.2017.09.003

Cited by 17 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the process of building main body model, the design options need to meet the needs of personality and hobbies. At the same time, the model also needs to set up the necessary neural network branches and horizontal and vertical iterative algorithm branches to increase the characteristics of different places [26][27][28][29][30]. After determining the best parameters, the images of the intelligent simulation model are automatically classified, and a total of 400 samples are collected, covering computer animation, black and white performance, computer performance, and so on.…”

Section: Experimental Design Of Children's Psychological Path Selection Model Based On Chaotic Neural Network Algorithmmentioning

confidence: 99%

[Retracted] Intelligent Simulation of Children’s Psychological Path Selection Based on Chaotic Neural Network Algorithm

Wang

2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

In recent years, there are many problems in the study of intelligent simulation of children’s psychological path selection, among which the main problem is to ignore the factors of children’s psychological path selection. Based on this, this paper studies the application of chaotic neural network algorithm in children’s mental path selection. First, an intelligent simulation model for children’s mental path selection based on chaotic neural network algorithm is established; second, it will combine the network based on different types of visual analysis strategies. The model is used to analyze the influencing factors of children in different regions in the choice of psychological paths. Finally, experiments are designed to verify the actual application effect of the simulation model. The results show that compared with the current mainstream intelligent simulation methods with iterative loop algorithms as the core, it adopts the intelligent simulation model based on the chaotic neural network algorithm has a good classification effect. It can effectively select the optimal psychological path according to the differences in children’s personality and can adaptively classify children in different regions, and the experimental results are accurate. Compared with the traditional method, it is improved by at least 37%.

show abstract

Section: Experimental Design Of Children's Psychological Path Selection Model Based On Chaotic Neural Network Algorithmmentioning

confidence: 99%

[Retracted] Intelligent Simulation of Children’s Psychological Path Selection Based on Chaotic Neural Network Algorithm

Wang

2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…As we mentioned, there are many agent-based evolutionary art generation approaches. One example of approaches which are driven by figurative agents is Tae and Chang's work [23]. They proposed a multi-agent-based art production framework for generating artworks that contain highly complex dynamics.…”

Section: Background and Related Work Of Evolutionary Artmentioning

confidence: 99%

Pixel-Based Approach for Generating Original and Imitating Evolutionary Art

Wang¹,

Xie²

2020

Electronics

View full text Add to dashboard Cite

We proposed a pixel-based evolution method to automatically generate evolutionary art. Our method can generate diverse artworks, including original artworks and imitating artworks, with different artistic styles and high visual complexity. The generation process is fully automated. In order to adapt to the pixel-based method, a von Neumann neighbor topology-modified particle swarm optimization (PSO) is employed to the proposed method. The fitness functions of PSO are well prepared. Firstly, we come up with a set of aesthetic fitness functions. Next, the imitating fitness function is designed. Finally, the aesthetic fitness functions and the imitating fitness function are weighted into one single object function, which is used in the modified PSO. Both the original outputs and imitating outputs are shown. A questionnaire is designed to investigate the subjective aesthetic feeling of proposed evolutionary art, and the statistics are shown.

show abstract

“…To better the study of network synchronization phenomena, scholars have introduced the Kuramoto model [9], the Boid model [10], the Vicsek model [11], etc. The Kuramoto model is obtained based on Winfree research, which retains the conditions of the coupled-phase oscillator model and describes the dynamical characteristics of nonlinear network systems in the presence of coupled states in a very good approximation [9] Due to the significant advantages of the Kuramoto model in understanding system synchronization and stability, it has received widespread attention from scholars [12][13][14][15][16][17][18] Reference [15] considered cluster synchronization in oscillator networks with heterogenous Kuramoto dynamics and provided conditions for the asymptotic stability of cluster synchronization manifolds [16] investigated the Kuramoto-oscillator network synchronization with the sampled-data updating rule and derived the synchronization condition [17] solved the problem of the Kuramoto-oscillator network synchronization using event-triggered delay pulse control.…”

Section: Introductionmentioning

confidence: 99%

Stochastic synchronization of Kuramoto-oscillator network with pinning control

Zhu,

Li,

Sun

et al. 2024

Phys. Scr.

View full text Add to dashboard Cite

The issue of time cost for the Kuramoto-oscillator network synchronization has received widespread attention. However, there is no relevant research on the stochastic synchronization of the Kuramoto-oscillator network with partial uncontrollable oscillators. This article investigates the synchronization problem of the Kuramoto-oscillator network in noisy environments using the pinning control strategy and multilayer distributed control. Previous research requires control of all oscillators, which implies a great control cost. To reduce the control cost, the ﬁnite/ﬁxed time controllers with pinning control are designed to provide the conditions for synchronization in noisy environments, and then the upper bounds on the convergence time of the network are estimated. Finally, numerical simulations are performed to justify the theoretical conclusions.

show abstract

Artificial life based on boids model and evolutionary chaotic neural networks for creating artworks

Cited by 17 publications

References 29 publications

[Retracted] Intelligent Simulation of Children’s Psychological Path Selection Based on Chaotic Neural Network Algorithm

[Retracted] Intelligent Simulation of Children’s Psychological Path Selection Based on Chaotic Neural Network Algorithm

Pixel-Based Approach for Generating Original and Imitating Evolutionary Art

Stochastic synchronization of Kuramoto-oscillator network with pinning control

Contact Info

Product

Resources

About