The genome recombination of neuroevolution. by Wenbing Shi (5806160)

“…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …”

The principle of sample data augmentation. by Wenbing Shi (5806160)

“…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …”

The fitness of NANEAT model evolution. by Wenbing Shi (5806160)

“…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …”

The speciation of NANEAT model evolution. by Wenbing Shi (5806160)

“…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. First, sample features are applied to the transfer function using a pointwise intensity transformation to obtain new feature samples. …”

Partial behavioral switching. by Hiroyuki Ichijo (13891153)

On the left, Dice score result for the HCP experiment. by Thomas Durantel (20933812)

GMM-KVS method flowchart. by Jingnan Yan (20727331)

“…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …”

Collected demonstration trajectories. by Jingnan Yan (20727331)

“…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …”

Schematic diagram of the elbow method. by Jingnan Yan (20727331)

“…To address this challenge, this paper proposes a novel trajectory learning method for robotic arms that combines Gaussian Mixture Model with a k-value selection algorithm. The proposed approach leverages the principles of the elbow method along with the properties of exponential functions, correction terms, and weight adjustments to accurately determine the optimal k-value. …”

Payoff matrices of sensory–motor IBM. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Payoff matrices of non-sensory motor IBM. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Variables of simulations. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Grid world Program 1.txt (R script). by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Grid world Program 2.txt (R script). by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Sensory–Motor Program.nlogo (NetLogo program). by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

NetLogo world movie. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Nash equilibria Si of non-Sensory motor IBM. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Measurements of simulations. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Payoff matrices of grid world model. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”

Nash equilibria Si of grid world model. by Hiroyuki Ichijo (13891153)

“…These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. …”