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()
Exemple #4
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    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()
Exemple #5
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    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()