diff --git a/AutoPentest-DRL.py b/AutoPentest-DRL.py
new file mode 100644
index 0000000..6991282
--- /dev/null
+++ b/AutoPentest-DRL.py
@@ -0,0 +1,254 @@
+import os
+import sys
+import time
+import json
+import csv
+from jinja2 import Environment, PackageLoader, select_autoescape, FileSystemLoader
+import torch
+from random import choice
+
+# Files used in various operation modes
+TOPOLOGY_PATH = "MulVAL_P/"
+LOGICAL_ATTACK_TOPOLOGY = "logical_topology_1.P"
+GENERATION_TOPOLOGY_TEMPLATE = "topology_template.P" # also defined in Topology_generator/topo_proc.py
+GENERATION_TOPOLOGY_FINAL = "topology_generated.P"
+REAL_ATTACK_TOPOLOGY = "real_topology_1.P" # also defined in Nmap_scan/create_top.py
+
+# Lists of server data with vulnerabilties
+filedataList = []
+webdataList = []
+firedataList = []
+
+
+def createTemp_tem():
+    
+    env = Environment(loader=FileSystemLoader('./'+TOPOLOGY_PATH), autoescape=select_autoescape('P'))
+    template_gen = env.get_template(GENERATION_TOPOLOGY_TEMPLATE)
+
+    fileTemp = list(choice(filedataList))
+    webTemp = list(choice(webdataList))
+    fireTemp = list(choice(firedataList))
+
+    baiscFile = open('./' + TOPOLOGY_PATH + GENERATION_TOPOLOGY_FINAL, 'w')
+
+    basic_temp = template_gen.render(CVE_Id_Web=webTemp[3], Web_Module=webTemp[0], Web_Transport=webTemp[1],
+                                            Web_Port=webTemp[2], Web_Product=webTemp[4], 
+                                            CVE_Id_File=fileTemp[3], File_Module=fileTemp[0], 
+                                            File_Transport=fileTemp[1], File_Port=fileTemp[2],
+                CVE_Id_Fire=fireTemp[3], Fire_Module=fireTemp[0], Fire_Transport=fireTemp[1], 
+                                            Fire_Port=fireTemp[2], Fire_Product=fireTemp[4], )
+
+
+    baiscFile.write(basic_temp)
+    baiscFile.close() 
+    print("Saved logical topology in '{}'.".format(TOPOLOGY_PATH + GENERATION_TOPOLOGY_FINAL))
+
+
+def saveVul():
+
+    print('Open preprocessed server data...')
+    fileProcessFile = open('./Database/ProcessData/fileData_process.csv', 'r')
+    webProcessFile = open('./Database/ProcessData/webData_process.csv', 'r')
+    msProcessFile = open('./Database/ProcessData/MSData_process.csv', 'r')
+    fireProcessFile = open('./Database/ProcessData/fireData_process.csv', 'r')
+
+    fileProcessData = csv.reader(fileProcessFile)
+    webProcessData = csv.reader(webProcessFile)
+    msProcessData = csv.reader(msProcessFile)
+    fireProcessData = csv.reader(fireProcessFile)
+
+    for filedata in fileProcessData:
+
+        if filedata[1] == 'Permissions, Privileges, and Access Control ':
+            file_module = filedata[2]
+            file_transport = filedata[3]
+            file_port = filedata[4]
+            cve_id_file = filedata[0]
+            file_product = filedata[5]
+
+            filedataTuple = (file_module, file_transport, file_port, cve_id_file, file_product)
+            filedataList.append(filedataTuple)
+
+    webProcessFile.seek(0)
+    for webdata in webProcessData:
+
+        if webdata[1] == 'Permissions, Privileges, and Access Control ':
+            web_module = webdata[2]
+            web_transport = webdata[3]
+            web_port = webdata[4]
+            cve_id_web = webdata[0]
+            web_product = webdata[5]
+
+            webdataTuple = (web_module, web_transport, web_port, cve_id_web, web_product)
+            webdataList.append(webdataTuple)
+
+    fireProcessFile.seek(0)
+    for firedata in fireProcessData:
+
+        if firedata[1] == 'Permissions, Privileges, and Access Control ':
+            fire_module = firedata[2]
+            fire_transport = firedata[3]
+            fire_port = firedata[4]
+            cve_id_fire = firedata[0]
+            fire_product = firedata[5]
+
+            firedataTuple = (fire_module, fire_transport, fire_port, cve_id_fire, fire_product)
+            firedataList.append(firedataTuple)
+
+    fileProcessFile.close()
+    webProcessFile.close()
+    msProcessFile.close()
+    fireProcessFile.close()
+
+    print('Vulnerability information loaded.')
+
+
+def startTrain(model):
+    
+    if not os.path.exists('./DQN/saved_model'):
+        os.system('mkdir ./DQN/saved_model')
+
+    if os.path.exists('./DQN/saved_model/dqn_model.pt'):
+        os.system('rm ./DQN/saved_model/dqn_model.pt')
+        print("Removed previous DQN model in 'DQN/saved_model/dqn_model.pt'.")
+
+    if model == 'logical_attack':
+        print("Generate attack graph using MulVAL...")
+        os.system('rm -f ./mulval_result/*.*')
+        os.chdir('./mulval_result')
+        os.system('../repos/mulval/utils/graph_gen.sh ../' + TOPOLOGY_PATH + LOGICAL_ATTACK_TOPOLOGY + ' -v > /dev/null')
+        os.chdir('../')
+        os.chdir('./DQN')
+        print("Process attack graph into attack matrix...")
+        os.system('python3 ./confirm_path.py')
+        os.chdir('./learn')
+        status = os.system('python3 ./dqn_learn.py train')
+        os.chdir('../../')
+        if os.WIFSIGNALED(status):
+            print("Interrupted while conducting DQN training => exit")
+    elif model == 'logical_attack_gen':
+        print("Generate attack graph using MulVAL...")
+        os.system('rm -f ./mulval_result/*.*')
+        os.chdir('./mulval_result')
+        os.system('../repos/mulval/utils/graph_gen.sh ../' + TOPOLOGY_PATH + GENERATION_TOPOLOGY_FINAL + ' -v > /dev/null')
+        os.chdir('../')
+        os.chdir('./DQN')
+        print("Process attack graph into attack matrix...")
+        os.system('python3 ./confirm_path.py')
+        os.chdir('./learn')
+        status = os.system('python3 ./dqn_learn.py train')
+        os.chdir('../../')
+        if os.WIFSIGNALED(status):
+            print("Interrupted while conducting DQN training => exit")
+    elif model == 'nmap':
+        print("Process attack graph into attack matrix...")
+        os.chdir('./DQN')
+        os.system('python3 ./confirm_path.py')
+        os.chdir('./learn')
+        status = os.system('python3 ./dqn_learn.py nmap')
+        os.chdir('../../')
+        if os.WIFSIGNALED(status):
+            print("Interrupted while conducting DQN training => exit")
+
+
+def startTrainCode(model):
+
+    if model == 'logical_attack':
+        print("--------------------------------------------------------------------------------")
+        print("AutoPentest-DRL: Compute attack path for logical network...")
+        env = Environment(loader=FileSystemLoader('./'+TOPOLOGY_PATH), autoescape=select_autoescape('P'))
+        template = env.get_template(LOGICAL_ATTACK_TOPOLOGY)
+        startTrain('logical_attack')
+    elif model == 'logical_attack_gen':
+        print("--------------------------------------------------------------------------------")
+        print("AutoPentest-DRL: Load vulnerability information...")
+        saveVul()
+        print("--------------------------------------------------------------------------------")
+        print("AutoPentest-DRL: Populate topology with vulnerabilities...")
+        createTemp_tem()
+        print("--------------------------------------------------------------------------------")
+        print("AutoPentest-DRL: Compute attack path for generated logical network...")
+        startTrain('logical_attack_gen')
+
+
+def startTemCode():
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Create random topology using topology-generator...")
+    os.chdir('./Topology_generator/topology-generator')
+    os.system('python2 topo-gen.py -c ../topo-gen-config -o top_info')
+    print("Saved topology in 'Topology_generator/topology-generator/top_info_1.json'.")
+
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Convert random topology to MulVAL topology...")
+    os.chdir('../')
+    status = os.system('python3 topo_proc.py')
+    os.chdir('../')
+    if os.WEXITSTATUS(status) != 0:
+        print("AutoPentest-DRL: Random topology generation failed => abort")
+        return
+
+    startTrainCode('logical_attack_gen')
+
+
+def startRealAttackCode():
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Get vulnerabilities in target network using Nmap...")
+    os.chdir('./Nmap_scan')
+    status = os.system('python3 create_top.py')
+    if os.WEXITSTATUS(status) != 0:
+        print("AutoPentest-DRL: Nmap scanning failed => abort")
+        return
+
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Generate attack graph using MulVAL...")
+    os.system('rm -f ../mulval_result/*.*')
+    os.chdir('../mulval_result')
+    os.system('../repos/mulval/utils/graph_gen.sh ../Nmap_scan/attack.P -v')
+
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Compute attack path for real network...")
+    os.chdir('../')
+    startTrain('nmap')
+
+    print("--------------------------------------------------------------------------------")
+    print("AutoPentest-DRL: Perform penetration testing using Metasploit...")
+    os.chdir('./Penetration_tools')
+    os.system('python3 ./start_attack.py')
+    os.chdir('../')
+
+
+def start_function(model):
+
+    if model == 'logical_attack':
+        print("AutoPentest-DRL: Operation mode:  {}".format("Attack on logical network"))
+        print("AutoPentest-DRL: Target topology: {}".format(TOPOLOGY_PATH + LOGICAL_ATTACK_TOPOLOGY))
+        startTrainCode('logical_attack')
+    elif model == 'logical_attack_gen':
+        print("AutoPentest-DRL: Operation mode:  {}".format("Attack on generated logical network"))
+        print("AutoPentest-DRL: Target topology: {}".format(TOPOLOGY_PATH + GENERATION_TOPOLOGY_FINAL))
+        startTemCode()
+    elif model == 'real_attack':
+        print("AutoPentest-DRL: Operation mode:  {}".format("Attack on real network"))
+        print("AutoPentest-DRL: Target topology: {}".format(TOPOLOGY_PATH + REAL_ATTACK_TOPOLOGY))
+        startRealAttackCode()
+    else:
+        print("AutoPentest-DRL: ERROR: Unrecognized operation mode: {}".format(model))
+
+
+if __name__ == '__main__':
+    try:
+        print("################################################################################")
+        print("AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning")
+        print("################################################################################")
+        if len(sys.argv) != 2:
+            print("ERROR: The operation mode must be specified:")
+            print("       $ python3 ./AutoPentest-DRL.py <OPERATION_MODE>")
+            print("OPERATION MODES:")
+            print("       logical_attack:  Attack on logical network topology")
+            print("       real_attack:     Attack on real network topology")
+            sys.exit(2)
+        model = str(sys.argv[1])
+        start_function(model)
+    except KeyboardInterrupt:
+        print ("\nAutoPentest-DRL: Keyboard interrupt detected => end execution")
+        sys.exit(1)
diff --git a/CHANGES b/CHANGES
new file mode 100644
index 0000000..5dd229e
--- /dev/null
+++ b/CHANGES
@@ -0,0 +1,9 @@
+
+AutoPentest-DRL v0.1
+--------------------
+* First public release of AutoPentest-DRL, an automated penetration
+  testing framework based on Deep Reinforcement Learning (DRL)
+  techniques. The framework can determine the most appropriate attack
+  path for a given logical network, and can also be used to execute a
+  penetration testing attack on a real network via tools such as Nmap
+  and Metasploit.