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Updated documentation in car_racing.py (#1462)
* Fixed g constant for better accuracy * Updated documentation in car_racing.py * Update pendulum.py * Update car_racing.py
This commit is contained in:
Abhinav Sagar
pzhokhov
@@ -13,22 +13,22 @@ import pyglet
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from pyglet import gl
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# Easiest continuous control task to learn from pixels, a top-down racing environment.
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# Discreet control is reasonable in this environment as well, on/off discretisation is
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# Discrete control is reasonable in this environment as well, on/off discretization is
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# fine.
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#
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# State consists of STATE_W x STATE_H pixels.
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#
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# Reward is -0.1 every frame and +1000/N for every track tile visited, where N is
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# the total number of tiles in track. For example, if you have finished in 732 frames,
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# the total number of tiles visited in the track. For example, if you have finished in 732 frames,
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# your reward is 1000 - 0.1*732 = 926.8 points.
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#
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# Game is solved when agent consistently gets 900+ points. Track is random every episode.
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# Game is solved when agent consistently gets 900+ points. Track generated is random every episode.
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#
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# Episode finishes when all tiles are visited. Car also can go outside of PLAYFIELD, that
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# is far off the track, then it will get -100 and die.
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#
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# Some indicators shown at the bottom of the window and the state RGB buffer. From
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# left to right: true speed, four ABS sensors, steering wheel position, gyroscope.
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# left to right: true speed, four ABS sensors, steering wheel position and gyroscope.
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#
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# To play yourself (it's rather fast for humans), type:
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#
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@@ -49,7 +49,7 @@ WINDOW_H = 800
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SCALE = 6.0 # Track scale
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TRACK_RAD = 900/SCALE # Track is heavily morphed circle with this radius
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PLAYFIELD = 2000/SCALE # Game over boundary
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FPS = 50
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FPS = 50 # Frames per second
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ZOOM = 2.7 # Camera zoom
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ZOOM_FOLLOW = True # Set to False for fixed view (don't use zoom)
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@@ -81,22 +81,24 @@ class FrictionDetector(contactListener):
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if u2 and "road_friction" in u2.__dict__:
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tile = u2
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obj = u1
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if not tile: return
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if not tile:
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return
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tile.color[0] = ROAD_COLOR[0]
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tile.color[1] = ROAD_COLOR[1]
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tile.color[2] = ROAD_COLOR[2]
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if not obj or "tiles" not in obj.__dict__: return
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if not obj or "tiles" not in obj.__dict__:
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return
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if begin:
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obj.tiles.add(tile)
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#print tile.road_friction, "ADD", len(obj.tiles)
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# print tile.road_friction, "ADD", len(obj.tiles)
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if not tile.road_visited:
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tile.road_visited = True
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self.env.reward += 1000.0/len(self.env.track)
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self.env.tile_visited_count += 1
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else:
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obj.tiles.remove(tile)
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#print tile.road_friction, "DEL", len(obj.tiles) -- should delete to zero when on grass (this works)
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# print tile.road_friction, "DEL", len(obj.tiles) -- should delete to zero when on grass (this works)
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class CarRacing(gym.Env, EzPickle):
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metadata = {
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@@ -126,7 +128,8 @@ class CarRacing(gym.Env, EzPickle):
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return [seed]
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def _destroy(self):
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if not self.road: return
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if not self.road:
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return
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for t in self.road:
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self.world.DestroyBody(t)
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self.road = []
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@@ -149,8 +152,8 @@ class CarRacing(gym.Env, EzPickle):
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rad = 1.5*TRACK_RAD
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checkpoints.append( (alpha, rad*math.cos(alpha), rad*math.sin(alpha)) )
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#print "\n".join(str(h) for h in checkpoints)
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#self.road_poly = [ ( # uncomment this to see checkpoints
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# print "\n".join(str(h) for h in checkpoints)
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# self.road_poly = [ ( # uncomment this to see checkpoints
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# [ (tx,ty) for a,tx,ty in checkpoints ],
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# (0.7,0.7,0.9) ) ]
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self.road = []
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@@ -162,7 +165,7 @@ class CarRacing(gym.Env, EzPickle):
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track = []
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no_freeze = 2500
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visited_other_side = False
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while 1:
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while True:
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alpha = math.atan2(y, x)
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if visited_other_side and alpha > 0:
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laps += 1
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@@ -178,8 +181,10 @@ class CarRacing(gym.Env, EzPickle):
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failed = False
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break
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dest_i += 1
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if dest_i % len(checkpoints) == 0: break
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if not failed: break
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if dest_i % len(checkpoints) == 0:
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break
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if not failed:
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break
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alpha -= 2*math.pi
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continue
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r1x = math.cos(beta)
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@@ -189,26 +194,33 @@ class CarRacing(gym.Env, EzPickle):
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dest_dx = dest_x - x # vector towards destination
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dest_dy = dest_y - y
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proj = r1x*dest_dx + r1y*dest_dy # destination vector projected on rad
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while beta - alpha > 1.5*math.pi: beta -= 2*math.pi
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while beta - alpha < -1.5*math.pi: beta += 2*math.pi
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while beta - alpha > 1.5*math.pi:
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beta -= 2*math.pi
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while beta - alpha < -1.5*math.pi:
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beta += 2*math.pi
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prev_beta = beta
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proj *= SCALE
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if proj > 0.3: beta -= min(TRACK_TURN_RATE, abs(0.001*proj))
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if proj < -0.3: beta += min(TRACK_TURN_RATE, abs(0.001*proj))
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if proj > 0.3:
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beta -= min(TRACK_TURN_RATE, abs(0.001*proj))
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if proj < -0.3:
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beta += min(TRACK_TURN_RATE, abs(0.001*proj))
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x += p1x*TRACK_DETAIL_STEP
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y += p1y*TRACK_DETAIL_STEP
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track.append( (alpha,prev_beta*0.5 + beta*0.5,x,y) )
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if laps > 4: break
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if laps > 4:
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break
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no_freeze -= 1
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if no_freeze==0: break
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#print "\n".join([str(t) for t in enumerate(track)])
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if no_freeze==0:
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break
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# print "\n".join([str(t) for t in enumerate(track)])
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# Find closed loop range i1..i2, first loop should be ignored, second is OK
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i1, i2 = -1, -1
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i = len(track)
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while True:
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i -= 1
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if i==0: return False # Failed
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if i==0:
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return False # Failed
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pass_through_start = track[i][0] > self.start_alpha and track[i-1][0] <= self.start_alpha
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if pass_through_start and i2==-1:
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i2 = i
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@@ -287,7 +299,8 @@ class CarRacing(gym.Env, EzPickle):
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while True:
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success = self._create_track()
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if success: break
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if success:
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break
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if self.verbose == 1:
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print("retry to generate track (normal if there are not many of this messages)")
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self.car = Car(self.world, *self.track[0][1:4])
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@@ -311,7 +324,7 @@ class CarRacing(gym.Env, EzPickle):
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if action is not None: # First step without action, called from reset()
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self.reward -= 0.1
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# We actually don't want to count fuel spent, we want car to be faster.
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#self.reward -= 10 * self.car.fuel_spent / ENGINE_POWER
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# self.reward -= 10 * self.car.fuel_spent / ENGINE_POWER
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self.car.fuel_spent = 0.0
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step_reward = self.reward - self.prev_reward
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self.prev_reward = self.reward
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@@ -493,5 +506,6 @@ if __name__=="__main__":
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#plt.savefig("test.jpeg")
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steps += 1
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isopen = env.render()
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if done or restart or isopen == False: break
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if done or restart or isopen == False:
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break
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env.close()
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