Commit 2cedd22c authored by Jae Young Lee's avatar Jae Young Lee

Revert some changes in simple_intersection_env and maneuver_base.

parent 0593724d
...@@ -256,7 +256,7 @@ class SimpleIntersectionEnv(RoadEnv, EpisodicEnvBase): ...@@ -256,7 +256,7 @@ class SimpleIntersectionEnv(RoadEnv, EpisodicEnvBase):
ego_heading_towards_lane_centre = \ ego_heading_towards_lane_centre = \
kwargs.setdefault('ego_heading_towards_lane_centre', True) kwargs.setdefault('ego_heading_towards_lane_centre', True)
randomize_special_scenarios = \ randomize_special_scenarios = \
kwargs.setdefault('randomize_special_scenarios', True) kwargs.setdefault('randomize_special_scenarios', False)
if n_others_range[0] < 0: if n_others_range[0] < 0:
raise ValueError("the number of other vehicles has to be non-negative.") raise ValueError("the number of other vehicles has to be non-negative.")
......
...@@ -29,7 +29,7 @@ class ManeuverBase(EpisodicEnvBase): ...@@ -29,7 +29,7 @@ class ManeuverBase(EpisodicEnvBase):
# _extra_action_weights_flag = True); note that a cost is defined # _extra_action_weights_flag = True); note that a cost is defined
# as a negative reward, so a cost will be summed up to the reward # as a negative reward, so a cost will be summed up to the reward
# with subtraction. # with subtraction.
_cost_weights = ( 20.0*1e-3, 1.0*1e-3, 0.25*1e-3, 1.0*1e-3, _cost_weights = ( 1.0*1e-3, 1.0*1e-3, 0.25*1e-3, 1.0*1e-3,
100.0*1e-3, 0.1*1e-3, 0.25*1e-3, 0.1*1e-3) 100.0*1e-3, 0.1*1e-3, 0.25*1e-3, 0.1*1e-3)
_extra_r_terminal = None _extra_r_terminal = None
...@@ -49,7 +49,7 @@ class ManeuverBase(EpisodicEnvBase): ...@@ -49,7 +49,7 @@ class ManeuverBase(EpisodicEnvBase):
#: enable the property for low-level policy training only, if any. #: enable the property for low-level policy training only, if any.
# this flag is useful in low-level policy learning # this flag is useful in low-level policy learning
# (see maneuvers.py. In ManeuverBase, this plays no role). # (see maneuvers.py).
_enable_low_level_training_properties = False _enable_low_level_training_properties = False
#: the additional reward given to the high-level learner for choosing #: the additional reward given to the high-level learner for choosing
......
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