def __init__(self, lifespan=None, test=False):
"""
Initialize the world. Base it on the grid_1D world.
"""
Grid_1D_World.__init__(self, lifespan)
self.name = 'grid_1D_delay'
self.name_long = 'one dimensional grid world with delay'
print '--delayed'
self.MAX_DELAY = 4
self.future_reward = [0.] * self.MAX_DELAY
self.world_visualize_period = 1e6
def __init__(self, lifespan=None):
"""
Initialize the world. Base it on the grid_1D world.
"""
Grid_1D_World.__init__(self, lifespan)
self.name = 'grid_1D_delay'
self.name_long = 'one dimensional grid world with delay'
print '--delayed'
self.display_state = False
self.MAX_DELAY = 4
self.future_reward = [0.] * self.MAX_DELAY
def __init__(self, lifespan=None):
"""
Initialize the world. Base it on the grid_1D world.
Parameters
----------
lifespan : int
The number of time steps to continue the world.
"""
Grid_1D_World.__init__(self, lifespan)
self.name = 'grid_1D_delay'
self.name_long = 'one dimensional grid world with delay'
print '--delayed'
self.max_delay = 9
self.future_reward = [0.] * self.max_delay
self.world_visualize_period = 1e6
"""
agent_name = '_'.join((world.name, 'agent'))
agent = Agent(world.num_sensors,
world.num_actions,
agent_name=agent_name,
show=show)
if restore:
agent = agent.restore()
actions = np.zeros((world.num_actions, 1))
# Repeat the loop through the duration of the existence of the world
while (world.is_alive()):
sensors, reward = world.step(actions)
world.visualize(agent)
actions = agent.step(sensors, reward)
return agent.report_performance()
def profile():
print 'profiling BECCA\'s performance...'
cProfile.run('test(World(lifespan=profiling_lifespan), restore=True)',
'tester_profile')
p = pstats.Stats('tester_profile')
p.strip_dirs().sort_stats('time', 'cumulative').print_stats(30)
if __name__ == '__main__':
if profile_flag:
profile()
else:
test(World(lifespan=testing_lifespan), restore=True)
