JackM323
402c20dfb5
env cleanup
...
rewards adjustment
pybullet logic contained in SimManager
2026-08-04 21:03:53 +02:00
JackM323
acb3d671be
Reworked training
...
new reward/penalty system
learning phases with curriculum learning
new training parameters
cleanup of old code
better logging while training
multiple environments instead of robots (they could bumb into each other)
2026-08-03 22:27:26 +02:00
JackM323
5317ef1299
fixed env eval setup
2026-07-31 18:35:09 +02:00
JackM323
01f993d727
new default values for training
2026-07-31 14:17:22 +02:00
JackM323
61cb0150f0
Training uses new Robot.py
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new Metrics and SimManager for live training viewing
Robot.py usage added to machinelearning
2026-07-31 13:55:24 +02:00
JackM323
c5ca79a354
Machine Learning Trainer
...
Training environment to make a walk model for the hexapod
generated code that will be checked
2026-07-30 17:23:36 +02:00
JackM323