class_docstr: Agents that plays slighlty better than random on the 007 game.
class_docstr_tok: ["Agents","that","plays","slighlty","better","than","random","on","the","007","game","."]
code: def act(
      self,
      observation: tp.Any,
      reward: tp.Any,
      done: bool,
      info: tp.Optional[tp.Dict[tp.Any, tp.Any]] = None,
  ) -> tp.Any:
      (
          my_amm,
          my_prot,
          their_amm,
          their_prot,
      ) = observation  # pylint: disable=unused-variable
      if their_prot == 4 and my_amm:
          action = "fire"
      elif their_amm == 0:
          action = np.random.choice(["fire", "reload"])
      else:
          action = np.random.choice(["fire", "protect", "reload"])
      return envs.JamesBond.actions.index(action)
  
imports: import warnings
  import operator
  import copy
  import typing
  import gym
  import numpy
  from nevergrad.common.tools import pytorch_import_fix
  from nevergrad.parametrization import parameter
  from ..base import ExperimentFunction
  from .None import base
  from .None import envs
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.utils.data import WeightedRandomSampler
label_desc: Use image node_id 2 for calling the Agent007 obj's underlying member method code with example usage: obj.act(observation, reward, done, info) and returns: envs