Group role assignment with flexible formation based on the genetic algorithm

Author(s):  
Zhu Xianjun ◽  
Xiao Fangxiong ◽  
Haibin Zhu ◽  
Wu Qilin ◽  
Zhou Xianzhong ◽  
...  
2011 ◽  
Vol 143-144 ◽  
pp. 274-278
Author(s):  
Yu Feng Wang ◽  
Li Di Wang ◽  
Ting Zhe Zhou

Robot Soccer provides a good experimental platform for the automatic control, artificial intelligence, robotics and other researches. A soccer robot system is also a typical multi-agent systems(MAS). Every robot in a soccer team is an agent,so the collaboration between agents, the rational apportionment of the robots' roles and the capacity for actions of the robots is the key to winning game. We present a strategy which is based on dynamic programming algorithm and genetic algorithm. Every robot has fitness to each role through which to carry out the dynamic role assignment, meanwhile, the parameters of the fitness functions could be optimized by genetic algorithm.


2018 ◽  
Vol 8 (1) ◽  
pp. 1-10
Author(s):  
Stuart D. H. Beveridge ◽  
Simon T. Henderson ◽  
Wayne L. Martin ◽  
Joleah B. Lamb

Abstract. Compared with other team settings, flight crew in air transport present a unique situation where the leader or supervisor regularly engages in active control. When the captain is assigned cognitively demanding pilot flying duties, the subordinate and often less experienced first officer must perform equally crucial monitoring and support duties. Using a systematic review methodology, this study reviews the reported effect of crew role assignment on flight safety outcomes. Our review identified 18 relevant studies and suggests crew performance factors linked to flight safety are affected by crew role assignment. Findings suggest a greater number of inherent obstacles may exist for optimal crew performance with the captain as pilot flying, raising the need for further specific research and policy review in this area.


1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan

Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.


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