Evolution of a self-organizing robot soccer team

This video shows the evolution of coordinated behavior of simulated robot soccer players. In the simulation, each soccer player is controlled by a neural network. The neural networks are evolved using an evolutionary algorithm, so generation after generation the strategy improves.
The corresponding paper "Evolving neural network controllers for a team of self-organizing robots" is available at http://www.demesos.tk

Category:

Science & Technology

Tags:

• research
• self-organization
• evolution
• neural networks
• robot soccer
• simulation

[visualeffectschannel]

Does it evolve like: the losing team will just be forgotten? Or how do you exactly let them evolve?

[Wil162]

@visualeffectschannel The teams of one generation (typically around 30 teams) play a tournament to determine a ranking among the teams. The top teams are kept, the worse ones are removed and replaced by variations (mutations and recombinations) of the remaining teams.

[gedq]

Germans. Even their bloody computers play football better than us.

[Wil162]

@gedq The research was done in Austria, not Germany. The computer plays definitely better than Austrian team ;-)

[60moments]

Let's see generation 1000!

[Melehete]

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[anakmudajaman]

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[bebeheuy]

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[Mjhond]

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[AntoMelta]

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[willamricard]

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[imegatrone]

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[siscia12]

Azzz...i feeling like blue XD

[cireneikual]

lol it says "Skiinet Simulator" at the top left!

[B3ss0R]

@Leoz2569 actually N,S,E and W just a direction vector where N = 0 degree S = 180 degree E = -90 degree and W = 90 degree... but when you deal with distance u need use trigonometry for example the ball are between N and E, so what u need to do are, get a ball coordinate and robot coordinate. and N and S will be y-axis and W and E will be x-axis, so just use theorem phytogoras to get the distance....