New Method for Estimating Form Defect of a Feature by Coupling the Genetic Algorithm and the Interior Points Method: Case of Flatness

2020 ◽  
pp. 286-291
Author(s):  
Mohamed Zeriab Es Sadek ◽  
Abdelilah Jalid
Keyword(s):  
Genetic Algorithm ◽  
New Method ◽  
Interior Points

scholarly journals Strategic Team AI Path Plans: Probabilistic Pathfinding

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Tng C. H. John ◽  
Edmond C. Prakash ◽  
Narendra S. Chaudhari
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computer Games ◽  
Fitness Function ◽  
New Method ◽  
High Quality ◽  
Plan Generation ◽  
Novel Method ◽  
Games And Simulations

This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

Incremental Hyperplane Partitioning for Classification

2013 ◽  
Vol 4 (2) ◽  
pp. 67-79 ◽  
Author(s):  
Tao Yang ◽  
Sheng-Uei Guan ◽  
Jinghao Song ◽  
Binge Zheng ◽  
Mengying Cao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Linear Equations ◽  
Curse Of Dimensionality ◽  
Experimental Results ◽  
New Method ◽  
Complex Pattern ◽  
Classification Problems ◽  
Encoding Scheme ◽  
Incremental Approach ◽  
Higher Dimensional

The authors propose an incremental hyperplane partitioning approach to classification. Hyperplanes that are close to the classification boundaries of a given problem are searched using an incremental approach based upon Genetic Algorithm (GA). A new method - Incremental Linear Encoding based Genetic Algorithm (ILEGA) is proposed to tackle the difficulty of classification problems caused by the complex pattern relationship and curse of dimensionality. The authors solve classification problems through a simple and flexible chromosome encoding scheme, where the partitioning rules are encoded by linear equations rather than If-Then rules. Moreover, an incremental approach combined with output portioning and pattern reduction is applied to cope with the curse of dimensionality. The algorithm is tested with six datasets. The experimental results show that ILEGA outperform in both lower- and higher-dimensional problems compared with the original GA.

Optimizing Fourier Series Based Gaits for Modular Robots Using an Evolutionary Algorithm

2013 ◽  
Author(s):  
David Ko ◽  
Harry H. Cheng
Keyword(s):  
Genetic Algorithm ◽  
Fourier Series ◽  
Evolutionary Algorithm ◽  
Periodic Motion ◽  
Degrees Of Freedom ◽  
Series Representation ◽  
Robotic System ◽  
Experimental Results ◽  
New Method ◽  
Modular Robots

A new method of controlling and optimizing robotic gaits for a modular robotic system is presented in this paper. A robotic gait is implemented on a robotic system consisting of three Mobot modules for a total of twelve degrees of freedom using a Fourier series representation for the periodic motion of each joint. The gait implementation allows robotic modules to perform synchronized gaits with little or no communication with each other making it scalable to increasing numbers of modules. The coefficients of the Fourier series are optimized by a genetic algorithm to find gaits which move the robot cluster quickly and efficiently across flat terrain. Simulated and experimental results show that the optimized gaits can have over twice as much speed as randomly generated gaits.

Energy-Balanced Routing Method for Wireless Cooperative Wireless Network

2013 ◽  
Vol 774-776 ◽  
pp. 1659-1663
Author(s):  
Yan Xin Yao ◽  
Qiu Shi Liu
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Wireless Network ◽  
Fitness Function ◽  
Path Loss ◽  
New Method ◽  
Transmission Path ◽  
Routing Method ◽  
Energy Balanced Routing

This paper presents a new method for optimizing energy consumption of wireless network. This new method tries to keep the energy consumption of the whole network while balancing the energy consumption of each node. In particular, we focus on the routing method to shorten the transmission path for reducing the energy path loss. We perform this by introducing an appropriate fitness function with the Genetic Algorithm. This fitness function is designed in a dedicate way so that the energy consumption minimization and energy consumption balance between nodes could be fulfilled simultaneously. Simulations validate that the proposed method could keep energy consumption and balance the energy consumption simultaneously to a better extent.

Shape Modification of NURBS Curves Using Genetic Algorithm

2012 ◽  
Vol 532-533 ◽  
pp. 1450-1454
Author(s):  
Yan Hong Li ◽  
Guo Wang Mu ◽  
Zeng Guo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Experimental Results ◽  
New Method ◽  
Shape Modification ◽  
Nurbs Curve ◽  
Nurbs Curves

In this paper, we propose a new method for shape modification of NURBS curves. For a given NURBS curve, we modify its one or more weights so that the curve passes through the point specified in advance. We convert this into an optimization problem and solve it by genetic algorithm. The experimental results show the feasibility and validity of our method.

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