hav4ik / tinyai Goto Github PK
View Code? Open in Web Editor NEWA compact implementation of NEAT (NeuroEvolution of Augmentic Topologies) algorithm on C++ for small programs/projects.
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Large number of nodes in solution
I'm wondering what the status is of this project; is it considered to be working as described in Ken Stanley's paper? The reason I'm asking is that when I run the "xor" experiment, the resulting network typically has around 20 hidden nodes, whereas in the paper it's stated that "NEAT very consistently uses 1 or 2 hidden nodes to build an XOR network".
Is this implementation based on / inspired by some other implementation, or implemented from scratch from the paper? Is there any other way to verify that it works as intended? Thanks!
Click to see an example of a network produced by the xor experiment
non-recurrent
24
1 4
5 -1.60176 2 1.9577 9 -0.0896985 2 0.668721
1 0
2 8
0 -0.40958 1 -0.150364 3 -0.110997 4 1.60981 5 -1.48269 7 -1.8749 6 1.40913 18 -0.150364
0 7
1 -0.0912658 4 -1.51859 0 -0.449885 5 -0.177615 6 -1.19628 14 1.27212 12 -1.86968
0 4
0 -0.0975539 8 1.48903 7 -1.82679 12 1.1046
0 4
7 1.29259 0 0.918139 8 -1.32898 22 0.918139
0 3
5 -1.99141 15 -1.21041 14 -0.418487
0 5
1 -0.673895 10 0.0527143 11 1.48281 17 -1.30425 0 -1.581
0 3
0 0.998239 13 0.994958 1 -1.97802
0 2
2 0.866348 7 -1.38062
0 0
0 2
10 1.88048 17 1.12631
0 1
1 0.64485
0 2
10 1.02876 16 0.122552
0 1
5 -0.67357
0 0
0 2
10 1 11 1.73794
0 0
0 2
1 0.985758 0 1.70312
0 2
5 -1.51736 16 -0.815769
0 1
0 0.486592
0 1
4 1.47994
0 1
0 1
0 1
7 -0.535213
Add gpu support?
It would accelerate the processing time to add gpu support to this implementation. Especially for large data sets
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