parameters: (self, config)
docstring: Creates an instance of the RandomTaxiCurriculum level.
  
      This coin game gives extra reward for finding the goal pano, and resets the
      goal once the goal has been found (or on timeout). Panos can be assigned
      rewards (coins) randomly and the agent will receive the reward the first
      time they visit these panos. Goal panos are assigned within a circle whose
      radius grows in time from min_goal_distance to max_goal_distance.
  
      Args:
        config: config dict of various settings.
docstring_summary: Creates an instance of the RandomTaxiCurriculum level.
docstring_tokens: Creates an instance of the RandomTaxiCurriculum level .
function: def __init__(self, config):
      """Creates an instance of the RandomTaxiCurriculum level.
  
      This coin game gives extra reward for finding the goal pano, and resets the
      goal once the goal has been found (or on timeout). Panos can be assigned
      rewards (coins) randomly and the agent will receive the reward the first
      time they visit these panos. Goal panos are assigned within a circle whose
      radius grows in time from min_goal_distance to max_goal_distance.
  
      Args:
        config: config dict of various settings.
      """
      super(CurriculumCourierGame, self).__init__(config)
      self._timestamp_start = config['timestamp_start_curriculum']
      self._annealing_rate = config['annealing_rate_curriculum']
      self._hours_curriculum_part_1 = config['hours_curriculum_part_1']
      self._hours_curriculum_part_2 = config['hours_curriculum_part_2']
      self._min_goal_distance = config['min_goal_distance_curriculum']
      self._max_goal_distance = config['max_goal_distance_curriculum']
      self._allowed_goal_distance = self._min_goal_distance
      assert self._timestamp_start <= time.time()
      assert self._annealing_rate > 0
      assert self._hours_curriculum_part_1 >= 0
      assert self._hours_curriculum_part_2 > 0
      assert self._min_goal_distance < self._max_goal_distance
  
      logging.info(
          'Curriculum: starts at t=%d, dist <= %f in P1 (%f h)',
          self._timestamp_start, self._min_goal_distance,
          self._hours_curriculum_part_1)
      logging.info(
          'Curriculum: then %f < dist <= %f in P2 (%f h)',
          self._min_goal_distance, self._max_goal_distance,
          self._hours_curriculum_part_2)
      logging.info('Curriculum: annealing rate: %f', self._annealing_rate)
function_tokens: def __init__ ( self , config ) : super ( CurriculumCourierGame , self ) . __init__ ( config ) self . _timestamp_start = config [ 'timestamp_start_curriculum' ] self . _annealing_rate = config [ 'annealing_rate_curriculum' ] self . _hours_curriculum_part_1 = config [ 'hours_curriculum_part_1' ] self . _hours_curriculum_part_2 = config [ 'hours_curriculum_part_2' ] self . _min_goal_distance = config [ 'min_goal_distance_curriculum' ] self . _max_goal_distance = config [ 'max_goal_distance_curriculum' ] self . _allowed_goal_distance = self . _min_goal_distance assert self . _timestamp_start <= time . time ( ) assert self . _annealing_rate > 0 assert self . _hours_curriculum_part_1 >= 0 assert self . _hours_curriculum_part_2 > 0 assert self . _min_goal_distance < self . _max_goal_distance logging . info ( 'Curriculum: starts at t=%d, dist <= %f in P1 (%f h)' , self . _timestamp_start , self . _min_goal_distance , self . _hours_curriculum_part_1 ) logging . info ( 'Curriculum: then %f < dist <= %f in P2 (%f h)' , self . _min_goal_distance , self . _max_goal_distance , self . _hours_curriculum_part_2 ) logging . info ( 'Curriculum: annealing rate: %f' , self . _annealing_rate )