Cross validation over learning rate 5k

Number of epochs: 5000

Rewards are limited by a lower and upper limit. This might cause problems.

training.simrunner.RewardHandlerName.consider-all

Considers all sensors.
Calculates a reward after every step.

Positive rewarded actions.

Negative rewarded actions.

Rewards are calculated after every step and might be different from zero.

training.parallel.ParallelConfig.q-lr-0

L0L1L2L3L4L5L6L7L8L9
learning rate0.00010.00050.0010.0050.010.050.10.20.30.5
E0
epsilon0.1
D0
discount0.75

Results for: Q0-LR2 L0E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L1E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L2E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L3E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L4E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L5E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L6E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L7E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L8E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10
Results for: Q0-LR2 L9E0D0

q-values
video 0 video 1 video 2 video 3
video 4 video 5 video 6 video 7
video 8 video 9 video 10