QRW06 Cross validation for speed-bonus (L,E)

Problem QRW5: Still good solutions get lost after a time when using the 'speed-bonus' reward handler.

Goal: Find out if a more constant increase can be found

Run multiple trainings with the 'speed-bonus' reward handler and cross validate learning rate and epsilon. Use smaller values for learning rate and epsilon, as they promise more stability

epoch count: 10k

training.simrunner.RewardHandlerName.speed-bonus

Considers all simulation events for calculating the reward.

Possible simulation events created for an agent:

1. After every simulation step:

   • Pushed the opponent. Reward = +0.05
   • Is pushed by the opponent. Reward = -0.01

2. At simulation end:

   • Winner by pushing the opponent: Reward = 100 + t * 150
   • Looser without being pushed: Reward = -100 - t * 150
   • Looser being pushed: Reward: -10

(t * x) is the 'speed bonus'

t = 1 - (s / max_s)

s:     Number of steps when th simulation ended   
max_s: Max number of steps for a simulation

Means, the reward/penalty is higher the shorter the simulation ran. The agent gets a higher reward when fast pushing out the opponent, or a higher penalty when fast moving unforced out of the field.

training.parallel.ParallelConfig.q-rw-2

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