From 7d79433c05a578d2c2835756498048923f363313 Mon Sep 17 00:00:00 2001
From: zach dwiel <zach.dwiel@intel.com>
Date: Thu, 4 Apr 2019 11:54:18 -0400
Subject: [PATCH] remove unused parameter
 scale_external_reward_by_intrinsic_reward_value

---
 .gitignore                  | 2 +-
 rl_coach/agents/agent.py    | 7 ++-----
 rl_coach/base_parameters.py | 3 ---
 3 files changed, 3 insertions(+), 9 deletions(-)

diff --git a/.gitignore b/.gitignore
index 50bcf54..c0ace1d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -15,6 +15,7 @@ roboschool
 *.orig
 docs/site
 coach_env
+venv
 build
 rl_coach.egg*
 rl_coach_slim.egg*
@@ -32,4 +33,3 @@ trace_test*
 .cache/
 *.pyc
 coachenv
-
diff --git a/rl_coach/agents/agent.py b/rl_coach/agents/agent.py
index bbd9004..f497e14 100644
--- a/rl_coach/agents/agent.py
+++ b/rl_coach/agents/agent.py
@@ -895,10 +895,7 @@ class Agent(AgentInterface):
             transition = self.update_transition_before_adding_to_replay_buffer(transition)
 
             # merge the intrinsic reward in
-            if self.ap.algorithm.scale_external_reward_by_intrinsic_reward_value:
-                transition.reward = transition.reward * (1 + self.last_action_info.action_intrinsic_reward)
-            else:
-                transition.reward = transition.reward + self.last_action_info.action_intrinsic_reward
+            transition.reward = transition.reward + self.last_action_info.action_intrinsic_reward
 
             # sum up the total shaped reward
             self.total_shaped_reward_in_current_episode += transition.reward
@@ -1026,7 +1023,7 @@ class Agent(AgentInterface):
         self.total_reward_in_current_episode += transition.reward
         self.shaped_reward.add_sample(transition.reward)
         self.reward.add_sample(transition.reward)
-        
+
         # create and store the transition
         if self.phase in [RunPhase.TRAIN, RunPhase.HEATUP]:
             # for episodic memories we keep the transitions in a local buffer until the episode is ended.
diff --git a/rl_coach/base_parameters.py b/rl_coach/base_parameters.py
index e462e2b..815a78a 100644
--- a/rl_coach/base_parameters.py
+++ b/rl_coach/base_parameters.py
@@ -200,9 +200,6 @@ class AlgorithmParameters(Parameters):
         # distributed agents params
         self.share_statistics_between_workers = True
 
-        # intrinsic reward
-        self.scale_external_reward_by_intrinsic_reward_value = False
-
         # n-step returns
         self.n_step = -1  # calculate the total return (no bootstrap, by default)