def testAugmented():
from vgdl.core import VGDLParser
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.mdpmap import MDPconverter
from vgdl.agents import PolicyDrivenAgent
zelda_level2 = """
wwwwwwwwwwwww
wA wwk1ww w
ww ww 1 w
ww wwww+w
wwwww1ww www
wwwww 0 Gww
wwwwwwwwwwwww
"""
from examples.gridphysics.mazes.rigidzelda import rigidzelda_game
g = VGDLParser().parseGame(rigidzelda_game)
g.buildLevel(zelda_level2)
env = GameEnvironment(g,
visualize=False,
recordingEnabled=True,
actionDelay=150)
C = MDPconverter(g, env=env, verbose=True)
Ts, R, _ = C.convert()
print C.states
print Ts[0]
print R
env.reset()
agent = PolicyDrivenAgent.buildOptimal(env)
env.visualize = True
env.reset()
task = GameTask(env)
exper = EpisodicExperiment(task, agent)
exper.doEpisodes(1)
def testAugmented():
from vgdl.core import VGDLParser
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.mdpmap import MDPconverter
from vgdl.agents import PolicyDrivenAgent
zelda_level2 = """
wwwwwwwwwwwww
wA wwk1ww w
ww ww 1 w
ww wwww+w
wwwww1ww www
wwwww 0 Gww
wwwwwwwwwwwww
"""
from examples.gridphysics.mazes.rigidzelda import rigidzelda_game
g = VGDLParser().parseGame(rigidzelda_game)
g.buildLevel(zelda_level2)
env = GameEnvironment(g, visualize=False,
recordingEnabled=True, actionDelay=150)
C = MDPconverter(g, env=env, verbose=True)
Ts, R, _ = C.convert()
print C.states
print Ts[0]
print R
env.reset()
agent = PolicyDrivenAgent.buildOptimal(env)
env.visualize = True
env.reset()
task = GameTask(env)
exper = EpisodicExperiment(task, agent)
exper.doEpisodes(1)
def testRecordingToGif(human=False):
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.core import VGDLParser
from examples.gridphysics.mazes import polarmaze_game, maze_level_2
from vgdl.agents import PolicyDrivenAgent, InteractiveAgent
from vgdl.tools import makeGifVideo
game_str, map_str = polarmaze_game, maze_level_2
g = VGDLParser().parseGame(game_str)
g.buildLevel(map_str)
env = GameEnvironment(g,
visualize=human,
recordingEnabled=True,
actionDelay=200)
task = GameTask(env)
if human:
agent = InteractiveAgent()
else:
agent = PolicyDrivenAgent.buildOptimal(env)
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(1)
print res
actions = [a for _, a, _ in env._allEvents]
print actions
makeGifVideo(env, actions, initstate=env._initstate)
def test4():
""" Same thing, but animated. """
from examples.gridphysics.mazes.windy import windy_stoch_game, windy_level
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.interfaces import GameEnvironment, GameTask
from vgdl.agents import PolicyDrivenAgent
g = VGDLParser().parseGame(windy_stoch_game)
g.buildLevel(windy_level)
env = GameEnvironment(g, visualize=True, actionDelay=100)
task = GameTask(env)
agent = PolicyDrivenAgent.buildOptimal(env)
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(5)
print res
def test4():
""" Same thing, but animated. """
from examples.gridphysics.mazes.windy import windy_stoch_game, windy_level
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.interfaces import GameEnvironment, GameTask
from vgdl.agents import PolicyDrivenAgent
g = VGDLParser().parseGame(windy_stoch_game)
g.buildLevel(windy_level)
env = GameEnvironment(g, visualize=True, actionDelay=100)
task = GameTask(env)
agent = PolicyDrivenAgent.buildOptimal(env)
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(5)
print res
def testPolicyAgent():
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.core import VGDLParser
from examples.gridphysics.mazes import polarmaze_game, maze_level_2
from vgdl.agents import PolicyDrivenAgent
game_str, map_str = polarmaze_game, maze_level_2
g = VGDLParser().parseGame(game_str)
g.buildLevel(map_str)
env = GameEnvironment(g, visualize=False, actionDelay=100)
task = GameTask(env)
agent = PolicyDrivenAgent.buildOptimal(env)
env.visualize = True
env.reset()
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(2)
print res
def testPolicyAgent():
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.core import VGDLParser
from examples.gridphysics.mazes import polarmaze_game, maze_level_2
from vgdl.agents import PolicyDrivenAgent
game_str, map_str = polarmaze_game, maze_level_2
g = VGDLParser().parseGame(game_str)
g.buildLevel(map_str)
env = GameEnvironment(g, visualize=False, actionDelay=100)
task = GameTask(env)
agent = PolicyDrivenAgent.buildOptimal(env)
env.visualize = True
env.reset()
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(2)
print res
def testRecordingToGif(human=False):
from pybrain.rl.experiments.episodic import EpisodicExperiment
from vgdl.core import VGDLParser
from examples.gridphysics.mazes import polarmaze_game, maze_level_2
from vgdl.agents import PolicyDrivenAgent, InteractiveAgent
from vgdl.tools import makeGifVideo
game_str, map_str = polarmaze_game, maze_level_2
g = VGDLParser().parseGame(game_str)
g.buildLevel(map_str)
env = GameEnvironment(g, visualize=human, recordingEnabled=True, actionDelay=200)
task = GameTask(env)
if human:
agent = InteractiveAgent()
else:
agent = PolicyDrivenAgent.buildOptimal(env)
exper = EpisodicExperiment(task, agent)
res = exper.doEpisodes(1)
print res
actions = [a for _, a, _ in env._allEvents]
print actions
makeGifVideo(env, actions, initstate=env._initstate)