diff --git a/analysis/reward_discount_analysis.jl b/analysis/reward_discount_analysis.jl
index a7d6f1a..d6e2b25 100644
--- a/analysis/reward_discount_analysis.jl
+++ b/analysis/reward_discount_analysis.jl
@@ -11,7 +11,7 @@ function run_rl_prcesses_reward_discount(γs::AbstractVector)
 
     Threads.@threads for γ_ind in 1:n_γs
         γ = γs[γ_ind]
-        env_helper = ReCo.run_rl(;
+        env_helper, rl_dir = ReCo.run_rl(;
             EnvType=ReCo.OriginEnv,
             n_episodes=400,
             episode_duration=15.0,
diff --git a/src/RL/RL.jl b/src/RL/RL.jl
index 4bd7479..5490488 100644
--- a/src/RL/RL.jl
+++ b/src/RL/RL.jl
@@ -79,7 +79,7 @@ end
 """
     run_rl(EnvType; <keyword arguments>)
 
-Run a reinforcement learning process and return the environment helper.
+Run a reinforcement learning process and return the tuple (`env_helper`, `rl_dir`). `env_helper` is the environment helper and `rl_dir` is the path of the process directory relative to the directory `ReCo.jl`.
 
 # Arguments
 - `EnvType::Type{<:Env}`: Environment type. It has to be one of the environments named after the file names in the directory `ReCo.jl/RL/Envs`, for example: `LocalCOMEnv`. A description of an environment is included at the beginning of the corresponding file.
@@ -161,9 +161,10 @@ function run_rl(
 
     env_helper = gen_env_helper(env, env_helper_shared; args=env_helper_args)
 
-    parent_dir = "RL/" * process_dir
+    parent_dir = "RL/$process_dir"
+    rl_dir = "$(ReCo.DEFAULT_EXPORTS_DIR)/$parent_dir"
 
-    env_helper_path = ReCo.DEFAULT_EXPORTS_DIR * "/$parent_dir/env_helper.jld2"
+    env_helper_path = "$rl_dir/env_helper.jld2"
 
     # Pre experiment
     hook(PRE_EXPERIMENT_STAGE, agent, env)
@@ -208,7 +209,7 @@ function run_rl(
 
     JLD2.save_object(env_helper_path, env_helper)
 
-    return env_helper
+    return (env_helper, rl_dir)
 end
 
 function gen_state_space_labels(state_label::String, state_space::Vector{Interval})