Add push curriculum

python/ppo.py

   --train                    Whether to train model, or only run inference [default: False].
   --summary-freq=<n>         Frequency at which to save training statistics [default: 10000].
   --save-freq=<n>            Frequency at which to save model [default: 50000].
-  --gamma=<n>                Reward discount rate [default: 0.99].
+  --gamma=<n>                Reward discount rate [default: 0.995].
   --lambd=<n>                Lambda parameter for GAE [default: 0.95].
   --time-horizon=<n>         How many steps to collect per agent before adding to buffer [default: 2048].
   --beta=<n>                 Strength of entropy regularization [default: 1e-3].

python/unityagents/environment.py

                 .format(self._curriculum.get_lesson_number(),
                     ', '.join([str(x)+' -> '+str(config[x]) for x in config])))
         else:
-            logger.info("\nEpisode Reset. In Lesson {0} : \t{1}"
+            logger.info("\nAcademy Reset. In Lesson {0} : \t{1}"
                 .format(self._curriculum.get_lesson_number(),
                     ', '.join([str(x)+' -> '+str(config[x]) for x in config])))
         if self._loaded:

python/curricula/test.json

         "param2" : [100, 50, 20, 15],
         "param3" : [0.2, 0.3, 0.7, 0.9]
     }
-}
+}

python/curricula/push.json

+{
+    "measure" : "progress",
+    "thresholds" : [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
+    "min_lesson_length" : 1,
+    "signal_smoothing" : false, 
+    "parameters" : 
+    {
+        "object_size" : [2.0, 1.9, 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1]
+    }
+}