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I can't see any existing links, code or any version of dll for it (I assume the one by EzyMCP). If some-one has it then we could have a look.
It might be interesting to play with it in a general sense, but probably not directly for your AI program. You would need a large training set of data for it - (like thousands of human played games). Think of a neural net as a complex curve fitting type program, that finds the best fit by tuning coefficients to match a large set of training data.
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06-08-2024, 03:08 PM
(This post was last modified: 06-08-2024, 03:27 PM by litdev.)
Yes, I forgot about that one (it was originally by EzyMPC so I must have had the code for it at some point) - I haven't really used it and can't find any samples for it so it may be fun to look into it, but my comments about ANNs (Artificial Neural Nets) in general and to your AI program will still apply.
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A couple of notes regarding ANN extension, if anyone is interested in maybe using this extension for something more serious.
1] The inputs and outputs both need to be normalised to be between 0 and 1.
2] Corrected a couple bugs (using text training data, 2 issues) and added option to set non-binary output - need to update using extension manager.
Here is my test code (a little tougher than XOr training, but not so much really), averaging 2 integers between 1 and 100, ZWWL934.000.
Results running 10 tests using ANN after traning with 10000 data points, the ANN results are in brackets.
Training started
epoch=1
Trained=1
BinaryOutput=False
Epoch=100000
LearningRate=0.7
Momentum=0.3
SigmoidResponse=1
ErrorRequired=0.0001
Mean(30,87) = 58.5 (59.467565069791200)
Mean(88,94) = 91 (83.865182777482700)
Mean(84,86) = 85 (81.174412270905500)
Mean(76,23) = 49.5 (48.755414992063700)
Mean(33,43) = 38 (35.396646012457900)
Mean(7,43) = 25 (23.578500109811300)
Mean(52,73) = 62.5 (63.828703608754200)
Mean(85,69) = 77 (76.402047305511200)
Mean(88,82) = 85 (81.147569198575100)
Mean(85,38) = 61.5 (62.70809712805100)
Press any key to continue...
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AB,
Great - go for it. I just fixed another small bug where Sigmoid cannot be set correctly.
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07-19-2024, 10:46 AM
(This post was last modified: 07-19-2024, 11:19 AM by litdev.)
AB,
My understanding is that training is usually done with data in a random order, but good for you to try different approaches.
Also, it is easier to trainl HSL->RGB rather than RGB->HSL. This is because Hue 0 is the same as 360 and 1 is very close to 359 etc. I had better results training RGB to Cos(H),Sin(H),S,L (all of cource normalised appropriately between 0 and 1).