>>>>>>> a7a19c68ba9116d31ce4ce6aa41b78dcd515d250
# specify which agent you want to use,
# BonsaiAgent that uses trained Brain or
# RandomAgent that randomly selects next action
agent = BonsaiAgent()
# hopper._env.render()
# hopper._env.reset()
episode_count = 100
try:
for i in range(episode_count):
# start a new episode and get the new state
hopper.episode_start()
state = hopper.get_state()
while True:
# get the action from the agent (based on the current state)
action = agent.act(state)
hopper._env.unwrapped.camera_adjust()
# do the next step of the simulation and get the new state
hopper.episode_step(action)
state = hopper.get_state()
if hopper.halted():
break
hopper.episode_finish("")