Added another potentially good neural net to effect matrix.
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@ -30,6 +30,8 @@ private:
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// const uint32_t _weights[36] = {0xbd8e626e, 0xbee2cd2c, 0x3e4d5cab, 0x3eceb8c3, 0xbed0a514, 0x3ec62438, 0x3e947ed4, 0xbe4b8bf2, 0xbf301113, 0xbf3f0a75, 0x3f1868f7, 0xbf0253ca, 0xbedca2f2, 0xbd547c6d, 0x3edd6a8a, 0xbd4b97b6, 0x3f64ec26, 0xbe5323c1, 0x3eccf87d, 0xbf2d4796, 0xbf62b6e8, 0xbf71daf6, 0xbf03f08e, 0xbf222609, 0x3e26c03c, 0xbf497837, 0xbee4d175, 0x3ec601de, 0x3e4e0695, 0x3eef2619, 0xbe849370, 0xbf18fb2b, 0x3f25bbd1, 0xbf3dcd78, 0x3f37a58d, 0x3ef4a25b};
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// Round 630, 221.0 points, length 38, 36% stopped, 64% died
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const uint32_t _weights[36] = {0xbd25943f, 0xbf279d81, 0x3e25d128, 0x3ec62438, 0x3f0e719c, 0x3eefbea9, 0x3e947ed4, 0xbe5323c1, 0xbf2d4796, 0xbf3f0a75, 0x3f0e45d9, 0xbf0253ca, 0xbedca2f2, 0xbd79073c, 0x3ede80ec, 0xbd4b97b6, 0x3f69a6be, 0xbe4b8bf2, 0x3eccf87d, 0xbf301113, 0xbf62b6e8, 0xbf71daf6, 0xbf204130, 0xbf222609, 0x3e26c03c, 0xbf497837, 0xbee4d175, 0x3ec601de, 0x3e4954eb, 0x3eef2619, 0xbe849370, 0xbf18fb2b, 0x3f25bbd1, 0xbf3b4e44, 0x3f484d59, 0x3edd6a8a};
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// Round 193, 164.8 points, length 36, 6% stopped, 94% died
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//const uint32_t _weights[36] = {0x3e872ffb, 0xbea57262, 0xbee269bf, 0x3ed790a3, 0xbf54014f, 0x3ecde0a6, 0xbf240a93, 0xbe9e4782, 0x3f205106, 0xbf4465c2, 0xbf79579a, 0xbf07f122, 0x3ed0e1bc, 0xbf7a5a09, 0xbf0fc70b, 0xbf6d1971, 0xbe0f5585, 0xbec94b12, 0x3f51f7a9, 0x3eaac42b, 0xbe6aafa6, 0x3d3e3ce3, 0xbf7c4232, 0xbe634103, 0x3f800000, 0x3eff886c, 0x3deae1e8, 0x3eea6988, 0xbf800000, 0xbf426a20, 0x3e3a0a45, 0xbe848803, 0x3e84e8c9, 0x3ef9fabc, 0xbe7733e6, 0xbecda633};
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const uint8_t _net_layout[3] = {6, 4, 3};
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const uint8_t _net_layers = 3;
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