Clean up env logging on initialization (#2950)

docs/Basic-Guide.md

 INFO:mlagents.envs:
 'Ball3DAcademy' started successfully!
 Unity Academy name: Ball3DAcademy
-        Number of Brains: 1
-        Number of Training Brains : 1
-        Reset Parameters :
+        Reset Parameters : {}
+INFO:mlagents.envs:Connected new brain:
 Unity brain name: 3DBallLearning
         Number of Visual Observations (per agent): 0
         Vector Observation space size (per agent): 8

docs/Learning-Environment-Executable.md

 Mono config path = '/Users/dericp/workspace/ml-agents/3DBall.app/Contents/MonoBleedingEdge/etc'
 INFO:mlagents.envs:
 'Ball3DAcademy' started successfully!
-INFO:mlagents.envs:
-'Ball3DAcademy' started successfully!
-        Number of Brains: 1
-        Number of Training Brains : 1
-        Reset Parameters :
+        Reset Parameters : {}
+INFO:mlagents.envs:Connected new brain:
 Unity brain name: Ball3DLearning
         Number of Visual Observations (per agent): 0
         Vector Observation space size (per agent): 8

ml-agents-envs/mlagents/envs/environment.py

                 )
 
     def __str__(self):
-        return (
-            """Unity Academy name: {0}
-        Number of Training Brains : {1}
-        Reset Parameters :\n\t\t{2}""".format(
-                self._academy_name,
-                str(self._num_external_brains),
-                "\n\t\t".join(
-                    [
-                        str(k) + " -> " + str(self._resetParameters[k])
-                        for k in self._resetParameters
-                    ]
-                ),
+        reset_params_str = (
+            "\n\t\t".join(
+                [
+                    str(k) + " -> " + str(self._resetParameters[k])
+                    for k in self._resetParameters
+                ]
-            + "\n"
-            + "\n".join([str(self._brains[b]) for b in self._brains])
+            if self._resetParameters
+            else "{}"
+        return f"""Unity Academy name: {self._academy_name}
+        Reset Parameters : {reset_params_str}"""
 
     def reset(
         self,
             agent_infos = output.rl_output.agentInfos[brain_param.brain_name]
             if agent_infos.value:
                 agent = agent_infos.value[0]
-                self._brains[brain_param.brain_name] = BrainParameters.from_proto(
-                    brain_param, agent
-                )
+                new_brain = BrainParameters.from_proto(brain_param, agent)
+                self._brains[brain_param.brain_name] = new_brain
+                logger.info(f"Connected new brain:\n{new_brain}")
         self._external_brain_names = list(self._brains.keys())
         self._num_external_brains = len(self._external_brain_names)