QMAP01 Cross validation mapping

number of epochs: 20k

Rewards are no longer limited by a lower and upper limit.

The ranges for learning rate, epsilon and discount were chosen from the results of Q-CV4

All values for mapping are used.

training.simrunner.RewardHandlerName.continuous-consider-all

Considers all simulation events for calculating the reward.

Possible simulation events created for an agent:

1. After every simulation step:

   • Pushed the opponent. Reward = +0.5
   • Is pushed by the opponent. Reward = -0.1

2. At simulation end:

   • Winner by pushing the opponent: Reward = 100 + t * 50
   • Looser without being pushed: Reward = -100 - t * 50
   • 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-map-0

Results for: QMAP01 L0E0D0M0

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Results for: QMAP01 L0E0D0M1

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Results for: QMAP01 L0E0D0M2

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Results for: QMAP01 L0E0D1M0

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Results for: QMAP01 L0E0D1M2

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Results for: QMAP01 L0E0D1M3

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