From 98dea01689ad4e5c391d0d391f12c361406cae73 Mon Sep 17 00:00:00 2001
From: Antonio Andriella <aandriella@iri.upc.edu>
Date: Sat, 14 Nov 2020 23:59:31 +0100
Subject: [PATCH] connect bn therapist model with the simulation irl
---
main.py | 38 +++++++++++++++++++-------------------
1 file changed, 19 insertions(+), 19 deletions(-)
diff --git a/main.py b/main.py
index 6cd75f2..f81f9f0 100644
--- a/main.py
+++ b/main.py
@@ -26,15 +26,15 @@ import pickle
import bnlearn
import argparse
-from cognitive_game_env import CognitiveGame
from episode import Episode
+from cognitive_game_env import CognitiveGame
from environment import Environment
-import src.maxent as M
-import src.plot as P
-import src.solver as S
-import src.optimizer as O
-import src.img_utils as I
-import src.value_iteration as vi
+import maxent as M
+import plot as P
+import solver as S
+import optimizer as O
+import img_utils as I
+import value_iteration as vi
import simulation as Sim
import bn_functions as bn_functions
@@ -246,8 +246,8 @@ def main():
#################GENERATE SIMULATION################################
parser = argparse.ArgumentParser()
- parser.add_argument('--bn_user_model_filename', '--bn_user_model', type=str,help="file path of the user bn model",
- default="/home/pal/Documents/Framework/bn_generative_model/bn_persona_model/persona_test.bif")
+ parser.add_argument('--bn_model_folder', '--bn_model_folder', type=str,help="folder in which all the user and the agent models are stored ",
+ default="/home/pal/Documents/Framework/GenerativeMutualShapingRL/BN_Models")
parser.add_argument('--bn_agent_model_filename', '--bn_agent_model', type=str,help="file path of the agent bn model",
default="/home/pal/Documents/Framework/bn_generative_model/bn_agent_model/agent_test.bif")
parser.add_argument('--epoch', '--epoch', type=int,help="number of epochs in the simulation", default=200)
@@ -262,9 +262,9 @@ def main():
default="/home/pal/carf_ws/src/carf/caregiver_in_the_loop/log")
parser.add_argument('--agent_patient_interaction_folder', '--api_path', type=str,help="agent-patient interaction folder",
default="/home/pal/carf_ws/src/carf/robot_in_the_loop/log")
- parser.add_argument('--user_id', '--id', type=int,help="user id")
- parser.add_argument('--with_feedback', '--f', type=bool,help="offering sociable")
- parser.add_argument('--session', '--s', type=int, help="session of the agent-human interaction")
+ parser.add_argument('--user_id', '--id', type=int,help="user id", required=True)
+ parser.add_argument('--with_feedback', '--f', type=eval, choices=[True, False], help="offering sociable", required=True)
+ parser.add_argument('--session', '--s', type=int, help="session of the agent-human interaction", required=True)
args = parser.parse_args()
@@ -276,8 +276,8 @@ def main():
epochs = args.epoch
runs = args.run
# initialise the agent
- bn_user_model_filename = args.bn_user_model_filename
- bn_agent_model_filename = args.bn_agent_model_filename
+ bn_user_model_filename = args.bn_model_folder +"/"+str(user_id)+"/"+str(with_feedback)+"/user_model.bif"
+ bn_agent_model_filename = args.bn_model_folder+"/"+str(user_id)+"/"+str(with_feedback)+"/agent_model.bif"
learned_policy_filename = args.output_policy_filename
learned_reward_filename = args.output_reward_filename
learned_value_f_filename = args.output_value_filename
@@ -314,10 +314,10 @@ def main():
output_folder_data_path = os.getcwd() + "/results/" + str(user_id) +"/"+str(with_feedback)+"/"+str(session)
if not os.path.exists(os.getcwd() + "/results"+"/"+str(user_id)):
os.mkdir(os.getcwd() + "/results"+"/"+str(user_id))
- if not os.path.exists(os.getcwd() + "/results"+"/"+str(user_id) +"/"+str(with_feedback)):
- os.mkdir(os.getcwd() + "/results" + "/" +str(user_id) +"/"+str(with_feedback))
- if not os.path.exists(output_folder_data_path):
- os.mkdir(output_folder_data_path)
+ if not os.path.exists(os.getcwd() + "/results"+"/"+str(user_id) +"/"+str(with_feedback)):
+ os.mkdir(os.getcwd() + "/results" + "/" +str(user_id) +"/"+str(with_feedback))
+ if not os.path.exists(output_folder_data_path):
+ os.mkdir(output_folder_data_path)
#1. CREATE INITIAL USER COGNITIVE MODEL FROM DATA
@@ -325,7 +325,7 @@ def main():
file_output=output_folder_data_path+"/summary_bn_variables_from_data.csv",
user_id=user_id,
with_feedback=with_feedback,
- rpi_folder_pathname=agent_patient_interaction_folder,
+ rpi_folder_pathname=None,#agent_patient_interaction_folder,
column_to_remove=None)
#2. CREATE POLICY FROM DATA
--
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