clean paths+remove dopamine

examples/load_config_and_play.py

 from animalai.envs.arena_config import ArenaConfig
 from animalai.envs.environment import AnimalAIEnvironment
 
-env_path = "/home/ben/AnimalAI/builds-ml-agents-aaio/aaio"  # TODO: 'exemples/env/aaio'
+env_path = "env/aaio"
 port = 5005
 configuration_file = "configurations/arena_configurations/hard/3-28-1.yml"
 configuration = ArenaConfig(configuration_file)

examples/train_baselines_dqn.py

@@ -7,7 +7,7 @@ from animalai.envs.arena_config import ArenaConfig
 def main():
     arenas_configurations = ArenaConfig("configurations/arena_configurations/train_ml_agents_arenas.yml")
     env = AnimalAIGym(
-        environment_filename="/home/ben/AnimalAI/builds-ml-agents-aaio/aaio",
+        environment_filename="env/aaio",
         worker_id=0,
         flatten_branched=True,
         uint8_visual=True,

examples/train_curriculum.py

@@ -4,11 +4,11 @@ from animalai_train.run_options_aai import RunOptionsAAI
 from animalai_train.run_training_aai import run_training_aai
 
 trainer_config_path = "configurations/training_configurations/train_ml_agents_config.yaml"
-environment_path = "/home/ben/AnimalAI/builds-ml-agents-aaio/aaio"
+environment_path = "env/aaio"
 curriculum_path = "configurations/curriculum"
 run_id = "train_curriculum"
-base_port = 5025
-number_of_environments = 16
+base_port = 5005
+number_of_environments = 8
 number_of_arenas_per_environment = 1
 
 args = RunOptionsAAI(

examples/train_ml_agents.py

@@ -5,7 +5,7 @@ from animalai_train.run_options_aai import RunOptionsAAI
 from animalai_train.run_training_aai import run_training_aai
 
 trainer_config_path = "configurations/training_configurations/train_ml_agents_config.yaml"
-environment_path = "/home/ben/AnimalAI/builds-ml-agents-aaio/aaio"
+environment_path = "env/aaio"
 arena_config_path = "configurations/arena_configurations/train_ml_agents_arenas.yml"
 run_id = "train_ml_agents"
 base_port = 5005