diff --git a/python/ray/rllib/ppo/loss.py b/python/ray/rllib/ppo/loss.py
index 8c15e68ff..e88b7fc7e 100644
--- a/python/ray/rllib/ppo/loss.py
+++ b/python/ray/rllib/ppo/loss.py
@@ -32,7 +32,7 @@ class ProximalPolicyLoss(object):
             # Do not split the last layer of the value function into
             # mean parameters and standard deviation parameters and
             # do not make the standard deviations free variables.
-            vf_config["free_logstd"] = False
+            vf_config["free_log_std"] = False
             with tf.variable_scope("value_function"):
                 self.value_function = ModelCatalog.get_model(
                     observations, 1, vf_config).outputs
diff --git a/test/jenkins_tests/run_multi_node_tests.sh b/test/jenkins_tests/run_multi_node_tests.sh
index 4c95851d1..ed50893f4 100755
--- a/test/jenkins_tests/run_multi_node_tests.sh
+++ b/test/jenkins_tests/run_multi_node_tests.sh
@@ -68,7 +68,7 @@ docker run --shm-size=10G --memory=10G $DOCKER_SHA \
     --env CartPole-v1 \
     --alg PPO \
     --num-iterations 2 \
-    --config '{"kl_coeff": 1.0, "num_sgd_iter": 10, "sgd_stepsize": 1e-4, "sgd_batchsize": 64, "timesteps_per_batch": 2000, "num_workers": 1}'
+    --config '{"kl_coeff": 1.0, "num_sgd_iter": 10, "sgd_stepsize": 1e-4, "sgd_batchsize": 64, "timesteps_per_batch": 2000, "num_workers": 1, "model": {"free_log_std": true}}'
 
 docker run --shm-size=10G --memory=10G $DOCKER_SHA \
     python /ray/python/ray/rllib/train.py \