Berserker

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 221.21 +/- 48.00
+      value: -817.34 +/- 267.34
       name: mean_reward
     task:
       type: reinforcement-learning

Ratata.zip

@@ -1,3 +1,3 @@
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Ratata/data

@@ -42,21 +42,21 @@
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If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. 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