def __init__(self, win):
self.ep = 0
self.ga = 2
self.al = 2
self.step_count = 0
self.__init_gui(win)
if robot_type == 'crawler':
self.robot = crawler.CrawlingRobot(self.canvas)
self.robot_environment = crawler.CrawlingRobotEnvironment(
self.robot)
else:
raise ValueError("Unknown RobotType")
# Init Agent
actionFn = lambda state: self.robot_environment.get_possible_actions(
state)
self.learner = agents_q_learning.QLearningAgent(actionFn=actionFn)
self.learner.set_epsilon(self.epsilon)
self.learner.set_learning_rate(self.alpha)
self.learner.set_discount(self.gamma)
# Start GUI
self.running = True
self.stopped = False
self.steps_to_skip = 0
self.thread = threading.Thread(target=self.run)
self.thread.start()
def __init__(self, win):
self.ep = 0
self.ga = 2
self.al = 2
self.stepCount = 0
# Init Gui
self.__initGUI(win)
# Init environment
if robotType == 'crawler':
self.robot = crawler.CrawlingRobot(self.canvas)
self.robotEnvironment = crawler.CrawlingRobotEnvironment(
self.robot)
elif robotType == 'pendulum':
self.robot = pendulum.PendulumRobot(self.canvas)
self.robotEnvironment = \
pendulum.PendulumRobotEnvironment(self.robot)
else:
raise ValueError('Unknown RobotType')
# Init Agent
def simulationFn(agent): return \
simulation.SimulationEnvironment(self.robotEnvironment, agent)
def actionFn(state): return \
self.robotEnvironment.getPossibleActions(state)
self.learner = qlearningAgents.QLearningAgent(actionFn=actionFn)
self.learner.setEpsilon(self.epsilon)
self.learner.setLearningRate(self.alpha)
self.learner.setDiscount(self.gamma)
# Start GUI
self.running = True
self.stopped = False
self.stepsToSkip = 0
self.thread = threading.Thread(target=self.run)
self.thread.start()
def __init__(self, win):
self.ep = 0
self.ga = 2
self.al = 2
self.step_count = 0
## Init Gui
self.__init_gui(win)
# Init environment
if robot_type == 'crawler':
self.robot = crawler.CrawlingRobot(self.canvas)
self.robot_environment = crawler.CrawlingRobotEnvironment(
self.robot)
elif robot_type == 'pendulum':
self.robot = pendulum.PendulumRobot(self.canvas)
self.robot_environment = \
pendulum.PendulumRobotEnvironment(self.robot)
else:
raise Exception("Unknown RobotType")
# Init Agent
simulation_fn = lambda agent: \
simulation.SimulationEnvironment(self.robot_environment, agent)
action_fn = lambda state: \
self.robot_environment.get_possible_actions(state)
self.learner = q_learning_agents.QLearningAgent(action_fn=action_fn)
self.learner.set_epsilon(self.epsilon)
self.learner.set_learning_rate(self.alpha)
self.learner.set_discount(self.gamma)
# Start GUI
self.running = True
self.stopped = False
self.steps_to_skip = 0
self.thread = threading.Thread(target=self.run)
self.thread.start()
def __init__(self, win):
self.ep = 0
self.ga = 2
self.al = 2
self.stepCount = 0
## Init Gui
self.__initGUI(win)
# Init environment
if robotType == 'crawler':
self.robot = crawler.CrawlingRobot(self.canvas)
self.robotEnvironment = crawler.CrawlingRobotEnvironment(
self.robot)
#elif robotType == 'pendulum':
# self.robot = pendulum.PendulumRobot(self.canvas)
# self.robotEnvironment = \
# pendulum.PendulumRobotEnvironment(self.robot)
else:
raise Exception("Unknown RobotType")
# Init Agent
#simulationFn = lambda agent: \
# simulation.SimulationEnvironment(self.robotEnvironment,agent)
actionFn = lambda state: \
self.robotEnvironment.getPossibleActions(state)
self.learner = qlearningAgents.QLearningAgent(actionFn=actionFn)
self.learner.setEpsilon(self.epsilon)
self.learner.setLearningRate(self.alpha)
self.learner.setDiscount(self.gamma)
# Start GUI
self.running = True
self.stopped = False
self.stepsToSkip = 0
self.thread = threading.Thread(target=self.run)
self.thread.start()
def __init__(self, win):
self.epsilon = 0.1
self.gamma = 0.8
self.alpha = 0.9
self.average_reward = 0
## Init Gui
self.__initGUI(win)
# Init environment
if robotType == 'crawler':
self.robot = crawler.CrawlingRobot(self.canvas)
self.robotEnvironment = crawler.CrawlingRobotEnvironment(self.robot)
elif robotType == 'pendulum':
self.robot = pendulum.PendulumRobot(self.canvas)
self.robotEnvironment = \
pendulum.PendulumRobotEnvironment(self.robot)
else:
raise "Unknown RobotType"
# Init Agent
self.learner = agent.QLearningAgent(self.robotEnvironment.getPossibleActions)
self.learner.setEpsilon(self.epsilon)
self.learner.setLearningRate(self.alpha)
self.learner.setDiscount(self.gamma)
# Start GUI
self.running = True
self.stopped = False
self.stepsToSkip = 0
self.thread = threading.Thread(target=self.run)
self.thread.start()
