# documentation files (the "Software"), to deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
from common import ENV_AGENT_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseTopDownStateBuilder
from malmopy.agent import RandomAgent
if __name__ == '__main__':
# Warn for Agent name !!!
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = RandomAgent(ENV_AGENT_NAMES[1], 3)
eval = PigChaseEvaluator(clients, agent, agent,
PigChaseTopDownStateBuilder())
eval.run()
eval.save('My Exp 1', 'pig_chase_results.json')
#
# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
from pathlib2 import Path
from common import ENV_AGENT_NAMES
from danish_puppet import DanishPuppet
from environment import PigChaseSymbolicStateBuilder
from evaluation import PigChaseEvaluator
from utility.util import ensure_folder
if __name__ == '__main__':
# Warn for Agent name !!!
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = DanishPuppet(ENV_AGENT_NAMES[1], helmets=[0, 1], use_markov=True)
eval = PigChaseEvaluator(clients, agent, agent, PigChaseSymbolicStateBuilder())
eval.run()
folder_path = Path("results", "evaluations")
ensure_folder(folder_path)
eval.save('My Exp 1', Path(folder_path, "pig_chase_results.json"))
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseTopDownStateBuilder, PigChaseSymbolicStateBuilder
from malmopy.agent import RandomAgent
from agent import PigChaseChallengeAgent, FocusedAgent
from json import dump
if __name__ == '__main__':
# Warn for Agent name !!!
name = 'Agent_1'
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = FocusedAgent(
ENV_AGENT_NAMES[1], ENV_TARGET_NAMES[0]
) ##Defines the type of agents that are going to be used
eval = PigChaseEvaluator(
clients, agent, agent,
PigChaseSymbolicStateBuilder()) ##Initializes the experiment
print('Simbolic state builder running')
eval.run()
eval.save('My Exp 1', '.')
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseSymoblicStateBuilder
from agent import PigChaseChallengeAgent, FocusedAgent
from malmopy.visualization import ConsoleVisualizer
if __name__ == '__main__':
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
builder = PigChaseSymbolicStateBuilder()
agent = FocusedAgent(ENV_AGENT_NAMES[1], ENV_TARGET_NAMES[0])
eval = PigChaseEvaluator(clients, agent, agent, builder)
eval.run()
eval.save('baseline_exp', 'baseline_results.json')
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
import sys, os
sys.path.append('../')
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseSymbolicStateBuilder
from malmopy.agent import RandomAgent
from agent import PigChaseChallengeAgent, FocusedAgent
from BayesAgent import BayesAgent
import tensorflow as tf
if __name__ == '__main__':
# Warn for Agent name !!!
config = tf.ConfigProto(allow_soft_placement=True)
config.gpu_options.allow_growth = True
with tf.Session(config = config) as sess:
agent = BayesAgent('Agent_2', ENV_TARGET_NAMES[0], 'Agent_1', False, sess)
if not agent.save:
sess.run(tf.global_variables_initializer())
print "Initialize"
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
eval = PigChaseEvaluator(clients, agent, agent, PigChaseSymbolicStateBuilder())
eval.run()
eval.save('HiDDeN Vs PigChaseChallenger', 'pig_chase_results')
from common import ENV_AGENT_NAMES
from evaluation import PigChaseEvaluator
from malmopy.agent import TemporalMemory, LinearEpsilonGreedyExplorer
from malmopy.environment.malmo import MalmoALEStateBuilder
from agent import PigChaseChallengeAgent, PigChaseQLearnerAgent
from malmopy.visualization import ConsoleVisualizer
from malmopy.model.chainer import QNeuralNetwork, ReducedDQNChain
if __name__ == '__main__':
device = -1
nb_actions = 3
visualizer = ConsoleVisualizer()
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
memory = TemporalMemory(100000, (18, 18))
chain = ReducedDQNChain((memory.history_length, 18, 18), nb_actions)
target_chain = ReducedDQNChain((memory.history_length, 18, 18), nb_actions)
model = QNeuralNetwork(chain, target_chain, device)
explorer = LinearEpsilonGreedyExplorer(0.6, 0.1, 1000000)
agent = PigChaseQLearnerAgent(ENV_AGENT_NAMES[1], nb_actions,
model, memory, 0.99, 32, 50000,
explorer=explorer, visualizer=visualizer)
#builder = MalmoALEStateBuilder()
builder = PigChaseTopDownStateBuilder(True)
eval = PigChaseEvaluator(clients, agent, agent, builder)
eval.run()
eval.save('qlearner_exp', 'qlearner_results.json')
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseSymbolicStateBuilder
from SandhogAgent import SandhogAgent
if __name__ == '__main__':
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = SandhogAgent(ENV_AGENT_NAMES[1], ENV_AGENT_NAMES[
0], ENV_TARGET_NAMES[0])
agent2 = SandhogAgent(ENV_AGENT_NAMES[1], ENV_AGENT_NAMES[
0], ENV_TARGET_NAMES[0])
builder = PigChaseSymbolicStateBuilder()
eval = PigChaseEvaluator(clients, agent, agent2, builder)
eval.run()
eval.save('sandhog_exp', 'sandhog_results.json')
# documentation files (the "Software"), to deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseSymbolicStateBuilder
from myagent import MyAgent
if __name__ == '__main__':
# Warn for Agent name !!!
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = MyAgent(ENV_AGENT_NAMES[1], ENV_TARGET_NAMES[0], ENV_AGENT_NAMES[0])
eval = PigChaseEvaluator(clients, agent, agent, PigChaseSymbolicStateBuilder())
eval.run()
eval.save('ParSys', 'pig_chase_results.json')
# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ===================================================================================================================
from common import ENV_AGENT_NAMES, ENV_TARGET_NAMES
from evaluation import PigChaseEvaluator
from environment import PigChaseTopDownStateBuilder, PigChaseSymbolicStateBuilder
from malmopy.agent import RandomAgent
from HogRiderQ import HogRiderQAgent
from agent import FocusedAgent
if __name__ == '__main__':
# Warn for Agent name !!!
clients = [('127.0.0.1', 10000), ('127.0.0.1', 10001)]
agent = HogRiderQAgent(ENV_AGENT_NAMES[1])
# we need PigChaseSymbolicStateBuilder
eval = PigChaseEvaluator(clients, agent, agent, PigChaseSymbolicStateBuilder())
eval.run()
eval.save('HogRider', 'pig_chase_HogRider.json')