Neural Network Tanks with PSO and GA

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Uploaded by on Nov 28, 2009

A little artificial intelligence project of mine which was written in C# with XNA Game Studio 3.0. The tanks in the simulation are autonomously controlled using an their own artificial neural networks. Instead of traditional back propagation for learning an evolutionary algorithm is used to adjust weights. A blue tank uses a genetic algorithm and the red tanks use particle swarm optimization. The video shows snap shots of some of the generations which last for just over a minute or so. Eventually during the later generations over fitting occurs and performance gain is negligible.

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Science & Technology

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Uploader Comments (adamstirtan)

  • nice work!! and great song. can u tell me what song it is?

  • @killz1510 Such Great Heights by Postal Service

  • @killz1510 Such great heights by postal service

  • Thanks, glad you liked it. Will be posting source code once it's done being cleaned up.

Video Responses

This video is a response to Genetic Algorithm Fish
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All Comments (14)

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  • @Kran000 In a very similar simulation I did, I used a function: fvision. The fvision's input is a pcaked information about "how the world is" in a cercle centered in yhe tank. The output is the direction. And the problem is how the functions works ;)

  • how do they sense their environment?

  • who win, PSO or GA? how does PSO get next generations? Nice works ;-)

  • Why not use gradient descent?

  • what signal those tanks use as an input? an angle to the closest gem? what architecture does the NN have?

  • nice, good work. Basically I just stare at XNA and wait for it to programme my ideas.

    Waiting patiently.......still nothing.

  • I am trying to create pretty much the same thing in XNA, but I am having lots of troubles. Would you be able to email or send me the XNA project so I can rip it apart and see how you did things? My neural networks learn but not nearly as well as they should according to other examples of this project I've seen done by other people.

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