def main():
filename = "learned_individuals_{0}".format(0)
rand_individual = Individual(data=filename, random=True)
agent = MyAgent(rand_individual)
task = MarioTask(agent.name, initMarioMode=2)
exp = EpisodicExperiment(task, agent)
print('Task Ready')
exp.doEpisodes(2)
print('mm 2:', task.reward)
task.env.initMarioMode = 1
exp.doEpisodes(1)
print('mm 1:', task.reward)
task.env.initMarioMode = 0
exp.doEpisodes(1)
print('mm 0:', task.reward)
task.env.initMarioMode = 0
exp.doEpisodes(1)
print('mm 0:', task.reward)
task.env.initMarioMode = 0
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print('mm 0, ld 5: ', task.reward)
task.env.initMarioMode = 1
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print('mm 1, ld 5: ', task.reward)
task.env.initMarioMode = 2
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print('mm 2, ld 5: ', task.reward)
print("finished")
def main():
clo = CmdLineOptions(sys.argv)
task = MarioTask(MarioEnvironment(clo.getHost(), clo.getPort(), clo.getAgent().name))
exp = EpisodicExperiment(clo.getAgent(), task)
exp.doEpisodes(3)
def main():
agent = ForwardAgent()
task = MarioTask(agent.name, initMarioMode = 2)
exp = EpisodicExperiment(task, agent)
print 'Task Ready'
exp.doEpisodes(2)
print 'mm 2:', task.reward
task.env.initMarioMode = 1
exp.doEpisodes(1)
print 'mm 1:', task.reward
task.env.initMarioMode = 0
exp.doEpisodes(1)
print 'mm 0:', task.reward
task.env.initMarioMode = 0
exp.doEpisodes(1)
print 'mm 0:', task.reward
task.env.initMarioMode = 0
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 0, ld 5: ', task.reward
task.env.initMarioMode = 1
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 1, ld 5: ', task.reward
task.env.initMarioMode = 2
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 2, ld 5: ', task.reward
print "finished"
def main():
agent = ForwardAgent()
task = MarioTask(agent.name, initMarioMode=2)
exp = EpisodicExperiment(task, agent)
print 'Task Ready'
exp.doEpisodes(2)
print 'mm 2:', task.reward
task.env.initMarioMode = 1
exp.doEpisodes(1)
print 'mm 1:', task.reward
task.env.initMarioMode = 0
exp.doEpisodes(1)
print 'mm 0:', task.reward
task.env.initMarioMode = 0
exp.doEpisodes(1)
print 'mm 0:', task.reward
task.env.initMarioMode = 0
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 0, ld 5: ', task.reward
task.env.initMarioMode = 1
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 1, ld 5: ', task.reward
task.env.initMarioMode = 2
task.env.levelDifficulty = 5
exp.doEpisodes(1)
print 'mm 2, ld 5: ', task.reward
print "finished"
def main():
f = open('try_3.txt','w')
agent = Ahude(IT,f)
distances = np.zeros([1])
data = np.zeros([1])
num_help = np.zeros([1])
mis_match = np.zeros([1])
#task = MarioTask(agent.name, initMarioMode = 2)
#exp = EpisodicExperiment(task, agent)
print 'Task Ready'
#task.env.initMarioMode = 2
#task.env.levelDifficulty = 1
task = MarioTask(agent.name, initMarioMode = 2)
exp = EpisodicExperiment(task, agent)
task.env.initMarioMode = 2
task.env.levelDifficulty = 1
if(agent.initialTraining):
exp.doEpisodes(2)
agent.newModel()
agent.saveModel()
else:
for i in range(ITERATIONS):
#IPython.embed()
#if( i == 2):
#agent.initialTraining = True;
# IPython.embed()
print "ITERATION",i
f.write('ITERATION %i \n' %i)
f.write('___________________________________________________\n')
rewards = exp.doEpisodes(1)
agent.updateModel()
if(agent._getName() == 'Ahude'):
num_help = np.vstack((num_help,np.array(agent.getNumHelp())))
mis_match = np.vstack((mis_match,np.array(agent.getMismatch())))
#agent.off = True
#rewards = exp.doEpisodes(1)
#agent.off = False
size = len(rewards[0])
distances = np.vstack((distances,np.array(rewards[0][size-1])))
data = np.vstack((data,np.array(agent.getNumData())))
agent.reset()
#agent.notComplete = False
print "TRACK COMPLETE"
#IPython.embed()
# IPython.embed()
f.close()
plt.figure(2)
plt.plot(data,distances)
if(agent._getName() == 'Ahude'):
plt.figure(1)
plt.plot(data,num_help)
plt.figure(3)
plt.plot(mis_match)
plt.show()
#agent.saveModel()
print "finished"
