diff --git a/RailEnvRLLibWrapper.py b/RailEnvRLLibWrapper.py
index e35a46e6e8b551a08ebd78b15029da25fb8c80ec..da54ad01f6d5536c0aab129509ae501f93e5ead9 100644
--- a/RailEnvRLLibWrapper.py
+++ b/RailEnvRLLibWrapper.py
@@ -13,7 +13,7 @@ class RailEnvRLLibWrapper(MultiAgentEnv):
                  # number_of_agents=1,
                  # obs_builder_object=TreeObsForRailEnv(max_depth=2)):
         super(MultiAgentEnv, self).__init__()
-        self.rail_generator = config["rail_generator"](nr_start_goal=config['number_of_agents'], min_dist=5,
+        self.rail_generator = config["rail_generator"](nr_start_goal=config['number_of_agents'], min_dist=5, nr_extra=30,
                                                        seed=config['seed'] * (1+config.vector_index))
         set_seed(config['seed'] * (1+config.vector_index))
         self.env = RailEnv(width=config["width"], height=config["height"], rail_generator=self.rail_generator,
diff --git a/experiment_configs/observation_benchmark/config.gin b/experiment_configs/observation_benchmark/config.gin
index 1fdadd2d4b4236978c1d2c7866c957683d106fd6..9f3c0727dd6b5a922b2a8b212e4bf5e6f77f0dab 100644
--- a/experiment_configs/observation_benchmark/config.gin
+++ b/experiment_configs/observation_benchmark/config.gin
@@ -1,6 +1,6 @@
 run_experiment.name = "observation_benchmark_results"
 run_experiment.num_iterations = 1002
-run_experiment.save_every = 200
+run_experiment.save_every = 100
 run_experiment.hidden_sizes = [32, 32]
 
 run_experiment.map_width = 20
diff --git a/train_experiment.py b/train_experiment.py
index d8154164e7abb69dd92dc726b4278d4caf0c16eb..68b45684bc4dcaf5efa190f731d03a436e94dbaa 100644
--- a/train_experiment.py
+++ b/train_experiment.py
@@ -34,7 +34,7 @@ from ray.rllib.models.preprocessors import TupleFlatteningPreprocessor
 
 ModelCatalog.register_custom_preprocessor("tree_obs_prep", CustomPreprocessor)
 ModelCatalog.register_custom_preprocessor("global_obs_prep", TupleFlatteningPreprocessor)
-ray.init()
+ray.init(object_store_memory=150000000000, redis_max_memory=30000000000)
 
 
 def train(config, reporter):
@@ -101,7 +101,7 @@ def train(config, reporter):
     trainer_config["horizon"] = config['horizon']
 
     trainer_config["num_workers"] = 0
-    trainer_config["num_cpus_per_worker"] = 8
+    trainer_config["num_cpus_per_worker"] = 10
     trainer_config["num_gpus"] = 0.5
     trainer_config["num_gpus_per_worker"] = 0.5
     trainer_config["num_cpus_for_driver"] = 2
@@ -155,7 +155,7 @@ def run_experiment(name, num_iterations, n_agents, hidden_sizes, save_every,
                 "seed": seed
                 },
         resources_per_trial={
-            "cpu": 10,
+            "cpu": 12,
             "gpu": 0.5
         },
         local_dir=local_dir