def distribute_bots(self, num_bots, bot_type):
"""distribute bots so that they don't overlap"""
# make a number of tiles to stick bots in
N_TILES = 10
tiles = [(r, c) for r in range(N_TILES) for c in range(N_TILES)]
random.shuffle(tiles)
bots_to_add = num_bots
while bots_to_add > 0:
(r, c) = tiles.pop() # random tile
x, y = r * constants.XDIM / float(
N_TILES), c * constants.YDIM / float(
N_TILES) # position within tile
x, y = x + random.random(
) * constants.XDIM * 0.5 / N_TILES, y + random.random(
) * constants.YDIM * 0.5 / N_TILES # random offset
if in_bounds(x, y):
agent_id = common.addObject(
bot_type,
OpenNero.Vector3f(x, y, 0),
scale=OpenNero.Vector3f(1, 1, 1),
type=constants.OBJECT_TYPE_ROOMBA,
collision=constants.OBJECT_TYPE_ROOMBA)
self.agent_ids.append(agent_id)
bots_to_add -= 1
else:
pass # if a tile caused a bad starting point, we won't see it again
def spawnAgent(self,
team=constants.OBJECT_TYPE_TEAM_0,
agent_xml=None,
first_person=True,
z_pos=2):
"""
This is the function ran when an agent already in the field
causes the generation of a new agent.
"""
if agent_xml is None:
color = 'blue'
if team is constants.OBJECT_TYPE_TEAM_1:
color = 'red'
agent_xml = "data/shapes/character/steve_still_%s.xml" % color
if first_person:
agent_pos = OpenNero.Vector3f(self.spawn_x[team],
self.spawn_y[team], z_pos)
self.curr_team = team
self.first_person_agent = common.addObject(agent_xml,
agent_pos,
type=team)
else:
pos = self.random_spawn_position(team)
agent_pos = OpenNero.Vector3f(pos[0], pos[1], z_pos)
common.addObject(agent_xml, agent_pos, type=team)
def mark(self, x, y, marker):
""" Mark a position (x, y) with the specified color """
# remove the previous object, if necessary
self.unmark(x, y)
# add a new marker object
id = common.addObject(marker, OpenNero.Vector3f(x, y, -1), OpenNero.Vector3f(0,0,0), OpenNero.Vector3f(0.5,0.5,0.5), type = constants.OBJECT_TYPE_MARKER)
# remember the ID of the object we are about to create
self.marker_map[(x, y)] = id
def addObject(templateFile,
position,
rotation=OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, 1, 1),
label="",
type=0,
collision=0):
return OpenNero.getSimContext().addObject(templateFile, position, rotation,
scale, label, collision, type)
def __init__(self, agent):
self.id = agent.state.id
self.agent = agent
self.pose = (0, 0, 0) # current x, y, heading
self.prev_pose = (0, 0, 0)
self.initial_position = OpenNero.Vector3f(0, 0, 0)
self.initial_rotation = OpenNero.Vector3f(0, 0, 0)
self.total_damage = 0
self.curr_damage = 0
def add_wall():
object_ids.append(
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(
location.x, location.y,
constants.HEIGHT + constants.OFFSET),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(1, 30, constants.HEIGHT),
type=1))
def change_flag(self, loc):
if self.flag_id:
common.removeObject(self.flag_id)
self.flag_loc = OpenNero.Vector3f(*loc)
self.flag_id = common.addObject("data/shapes/cube/BlueCube.xml",
self.flag_loc,
label="Flag",
scale=OpenNero.Vector3f(1, 1, 10),
type=constants.OBJECT_TYPE_FLAG)
def add_wall():
obj_id = common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(location.x, location.y,
constants.HEIGHT + constants.OFFSET),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(5, 30, constants.HEIGHT * 2),
type=1)
object_ids[obj_id] = set(['rotate', 'move', 'scale', 'remove'])
def set_environment(self, env):
self.environment = env
for id in self.wall_ids: # delete the walls
common.removeObject(id)
del self.wall_ids[:] # clear the ids
OpenNero.set_environment(env)
common.addObject("data/shapes/cube/WhiteCube.xml",
OpenNero.Vector3f(1 * constants.GRID_DX,
2 * constants.GRID_DY,
0 * constants.GRID_DZ),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(.25, .25, 4))
common.addObject("data/shapes/cube/WhiteCube.xml",
OpenNero.Vector3f(2 * constants.GRID_DX,
2 * constants.GRID_DY,
0 * constants.GRID_DZ),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(.25, .25, 4))
common.addObject("data/shapes/cube/WhiteCube.xml",
OpenNero.Vector3f(3 * constants.GRID_DX,
2 * constants.GRID_DY,
0 * constants.GRID_DZ),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(.25, .25, 4))
def start_tower1(self): #Problem reduction
""" start the tower demo """
self.num_disks = 3
OpenNero.disable_ai()
self.stop_agent()
env = TowerEnvironment()
env.initialize_blocks()
self.set_environment(env)
self.agent_id = common.addObject(
"data/shapes/character/BlocksRobot.xml",
OpenNero.Vector3f(constants.GRID_DX, constants.GRID_DY, 2),
type=constants.AGENT_MASK,
scale=OpenNero.Vector3f(3, 3, 3))
OpenNero.enable_ai()
def start_nlp_extended(): #Natural Language Processing
""" start the tower demo """
getMod().num_disks = 3
OpenNero.disable_ai()
getMod().stop_agent()
env = TowerEnvironment()
env.initialize_blocks()
getMod().set_environment(env)
getMod().agent_id = common.addObject(
"data/shapes/character/MyNLPRobot.xml",
OpenNero.Vector3f(TowerofHanoi.constants.GRID_DX,
TowerofHanoi.constants.GRID_DY, 2),
type=TowerofHanoi.constants.AGENT_MASK,
scale=OpenNero.Vector3f(3, 3, 3))
OpenNero.enable_ai()
def start_agent_state_space_search(self): #State-space search
""" start the tower demo """
self.num_disks = 3
OpenNero.disable_ai()
self.stop_agent()
env = TowerEnvironment()
env.initialize_blocks()
self.set_environment(env)
#self.set_environment(TowerEnvironment())
self.agent_id = common.addObject(
"data/shapes/character/BlocksRobot2.xml",
OpenNero.Vector3f(constants.GRID_DX, constants.GRID_DY, 2),
type=constants.AGENT_MASK,
scale=OpenNero.Vector3f(3, 3, 3))
OpenNero.enable_ai()
def start_my_planner_3_disk():
""" start the tower demo """
getMod().num_disks = 3
OpenNero.disable_ai()
getMod().stop_agent()
env = TowerEnvironment()
env.initialize_blocks()
getMod().set_environment(env)
getMod().agent_id = common.addObject(
"data/shapes/character/MyPlanningRobot3.xml",
OpenNero.Vector3f(TowerofHanoi.constants.GRID_DX,
TowerofHanoi.constants.GRID_DY, 2),
type=TowerofHanoi.constants.AGENT_MASK,
scale=OpenNero.Vector3f(3, 3, 3))
OpenNero.enable_ai()
def start_tower3(self): #2 Disk Goal Stack Planner
""" start the tower demo """
self.num_disks = 2
OpenNero.disable_ai()
self.stop_agent()
env = TowerEnvironment()
env.initialize_blocks()
self.set_environment(env)
#self.set_environment(TowerEnvironment())
self.agent_id = common.addObject(
"data/shapes/character/BlocksRobot3.xml",
OpenNero.Vector3f(constants.GRID_DX, constants.GRID_DY, 2),
type=constants.AGENT_MASK,
scale=OpenNero.Vector3f(3, 3, 3))
OpenNero.enable_ai()
def mouse_action():
import math
global modify_object_id
global object_ids
if len(modify_object_id) == 0:
return
sim_context = OpenNero.getSimContext()
cursor = sim_context.getMousePosition()
location = sim_context.getClickedPosition(cursor.x, cursor.y)
if 'move' in modify_object_id:
sim_context.setObjectPosition(
modify_object_id['move'],
OpenNero.Vector3f(location.x, location.y,
constants.HEIGHT + constants.OFFSET))
if 'rot' in modify_object_id:
position = sim_context.getObjectPosition(modify_object_id['rot'])
angle = math.atan2(location.x - position.x, location.y - position.y)
sim_context.setObjectRotation(
modify_object_id['rot'],
OpenNero.Vector3f(0, 0, -math.degrees(angle)))
if 'scale' in modify_object_id:
position = sim_context.getObjectPosition(modify_object_id['scale'])
rotation = sim_context.getObjectRotation(modify_object_id['scale'])
theta = math.radians(rotation.z)
# calculate mouse location in the frame of reference of the object
localx = (location.x - position.x) * math.cos(theta) + (
location.y - position.y) * math.sin(theta)
localy = -(location.x - position.x) * math.sin(theta) + (
location.y - position.y) * math.cos(theta)
# scale < 1 if local coordinate is -ve and scale > 1 otherwise
scalex = 1 + math.fabs(localx)
scaley = 1 + math.fabs(localy)
if localx < 0: scalex = 1 / scalex
if localy < 0: scaley = 1 / scaley
prev_scale = sim_context.getObjectScale(modify_object_id['scale'])
sim_context.setObjectScale(
modify_object_id['scale'],
OpenNero.Vector3f(scalex, scaley, prev_scale.z))
def evaluate_trace(self):
"""
evaluate agent and compute fitness based on trace information
"""
# flush network from previous activations
org = self.get_org()
org.net.flush()
environment = OpenNero.get_environment()
trace = environment.trace
# place the agent at the beginning of the trace
self.state.position = OpenNero.Vector3f(trace.position[0].x,
trace.position[0].y,
trace.position[0].z)
self.state.rotation = OpenNero.Vector3f(trace.rotation[0].x,
trace.rotation[0].y,
trace.rotation[0].z)
current_step = trace.initial_step
j = 0 # trace index at which error is calculated
while j < len(trace.position
) - 1 and current_step < environment.STEPS_PER_EPISODE:
self.state.position = position
self.state.rotation = rotation
sensors = environment.sense(self)
actions = self.network_action(sensors)
# error based on position - find index in trace where error based on
# current position starts to increase, i.e. starting with the current
# trace index, we find position in trace that is closest to the current
# state position.
error1 = trace.position[j].getDistanceFrom(position)
error2 = trace.position[j + 1].getDistanceFrom(position)
while error1 >= error2 and j < len(trace.position) - 2:
j += 1
error1 = error2
error2 = trace.position[j + 1].getDistanceFrom(position)
if error1 > self.ERROR_THRESHOLD:
break
# calculate new position, orientation, and velocity
self.environment.act(self, actions)
current_step += 1
self.passed_steps = j
return float(j) / len(trace.position)
def spawnAgent(self, team=constants.OBJECT_TYPE_TEAM_0, ai=None):
"""
This is the function ran when an agent already in the field
causes the generation of a new agent.
Returns the id of the spawned agent.
"""
if not self.environment:
return
if ai == 'rtneat' and not OpenNero.get_ai('rtneat-%s' % team):
self.start_rtneat(team)
if ai == 'rtneatq' and not OpenNero.get_ai('rtneatq-%s' % team):
self.start_rtneatq(team)
self.curr_team = team
color = constants.TEAM_LABELS[team]
dx = random.randrange(constants.XDIM / 20) - constants.XDIM / 40
dy = random.randrange(constants.XDIM / 20) - constants.XDIM / 40
return common.addObject(
"data/shapes/character/steve_%s_%s.xml" % (color, ai),
OpenNero.Vector3f(self.spawn_x[team] + dx, self.spawn_y[team] + dy,
2),
type=team)
def ClientMain():
# physics off, ai off by default
#disable_physics()
OpenNero.disable_ai()
if not module.getMod().setup_map():
inputConfig.switchToHub()
return
# add a light source
OpenNero.getSimContext().addLightSource(OpenNero.Vector3f(500, -500, 1000),
1500)
#common.addSkyBox("data/sky/irrlicht2")
# setup the gui
CreateGui(common.getGuiManager())
# add a camera
camRotateSpeed = 100
camMoveSpeed = 15000
camZoomSpeed = 200
cam = OpenNero.getSimContext().addCamera(camRotateSpeed, camMoveSpeed,
camZoomSpeed)
cam.setFarPlane(40000)
cam.setEdgeScroll(False)
recenter_cam = recenter(cam)
recenter_cam()
# create the io map
ioMap = inputConfig.createInputMapping()
ioMap.BindKey("KEY_SPACE", "onPress", recenter_cam)
OpenNero.getSimContext().setInputMapping(ioMap)
def spawn_agent(self, agent, x, y):
simId = common.addObject(
"data/shapes/character/steve_%s.xml" % (constants.TEAM_LABELS[agent.team_type]),
OpenNero.Vector3f(x, y, 2),
type=agent.team_type)
common.initObjectBrain(simId, agent)
return simId
def load_trace(self, filename):
'''
load previously pickled trace from the given file
'''
with open(filename, 'r') as file:
self.trace = pickle.load(file)
self.use_trace = True
for pos in self.trace.position:
id = common.addObject("data/shapes/cube/YellowCube.xml",
position=pos,
scale=OpenNero.Vector3f(0.25, 0.25, 0.25),
type=constants.OBJECT_TYPE_LEVEL_GEOM)
self.path_markers_trace.append(id)
def start_demonstration(self):
'''
start the keyboard agent to collect demonstration example
'''
OpenNero.disable_ai()
team = constants.OBJECT_TYPE_TEAM_0
self.curr_team = team
#self.environment.remove_all_agents(team)
location = (self.spawn_x[team], self.spawn_y[team], 2)
agnt = common.addObject("data/shapes/character/steve_keyboard.xml",
position=OpenNero.Vector3f(*location),
type=team)
OpenNero.enable_ai()
self.environment.start_tracing()
return agnt
def ClientMain():
global modify_object_id
global object_ids
global guiMan
OpenNero.disable_ai()
if not module.getMod().setup_map():
switchToHub()
return
# add a light source
OpenNero.getSimContext().addLightSource(OpenNero.Vector3f(500, -500, 1000),
1500)
common.addSkyBox("data/sky/irrlicht2")
# setup the gui
guiMan = common.getGuiManager()
object_ids = {}
modify_object_id = {}
# add a camera
camRotateSpeed = 100
camMoveSpeed = 15000
camZoomSpeed = 200
cam = OpenNero.getSimContext().addCamera(camRotateSpeed, camMoveSpeed,
camZoomSpeed)
cam.setFarPlane(40000)
cam.setEdgeScroll(False)
def recenter(cam):
def closure():
cam.setPosition(OpenNero.Vector3f(0, 0, 100))
cam.setTarget(OpenNero.Vector3f(100, 100, 0))
return closure
recenter_cam = recenter(cam)
recenter_cam()
# create the io map
ioMap = createInputMapping()
ioMap.BindKey("KEY_SPACE", "onPress", recenter_cam)
OpenNero.getSimContext().setInputMapping(ioMap)
def setup_map(self):
"""
setup the test environment
"""
OpenNero.disable_ai()
if self.environment:
error("Environment already created")
return
# create the environment - this also creates the rtNEAT object
self.environment = self.create_environment()
OpenNero.set_environment(self.environment)
# world walls
height = constants.HEIGHT + constants.OFFSET
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM / 2, 0, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH,
constants.XDIM,
constants.HEIGHT * 2),
label="World Wall0",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(0, constants.YDIM / 2, height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(constants.WIDTH,
constants.YDIM,
constants.HEIGHT * 2),
label="World Wall1",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM, constants.YDIM / 2,
height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(constants.WIDTH,
constants.YDIM,
constants.HEIGHT * 2),
label="World Wall2",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM / 2, constants.YDIM,
height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH,
constants.XDIM,
constants.HEIGHT * 2),
label="World Wall3",
type=constants.OBJECT_TYPE_OBSTACLE)
# Add an obstacle wall in the middle
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM / 2,
constants.YDIM / 2, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH,
constants.YDIM / 4,
constants.HEIGHT * 2),
label="World Wall4",
type=constants.OBJECT_TYPE_OBSTACLE)
# Add some trees
for i in (0.25, 0.75):
for j in (0.25, 0.75):
# don't collide with trees - they are over 500 triangles each
common.addObject("data/shapes/tree/Tree.xml",
OpenNero.Vector3f(i * constants.XDIM,
j * constants.YDIM,
constants.OFFSET),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, 1, 1),
label="Tree %d %d" % (10 * i, 10 * j),
type=constants.OBJECT_TYPE_LEVEL_GEOM)
# collide with their trunks represented with cubes instead
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(i * constants.XDIM, j * constants.YDIM,
constants.OFFSET),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, 1, constants.HEIGHT),
type=constants.OBJECT_TYPE_OBSTACLE)
# Add the surrounding Environment
common.addObject("data/terrain/NeroWorld.xml",
OpenNero.Vector3f(constants.XDIM / 2,
constants.YDIM / 2, 0),
scale=OpenNero.Vector3f(1.2, 1.2, 1.2),
label="NeroWorld",
type=constants.OBJECT_TYPE_LEVEL_GEOM)
return True
def place_basic_turret(self, loc):
return common.addObject("data/shapes/character/steve_basic_turret.xml",
OpenNero.Vector3f(*loc),
type=constants.OBJECT_TYPE_TEAM_1)
def sense(self, agent, observations):
"""
figure out what the agent should sense
"""
# the last observation is whether there is a target for the agent
# update: this is now being done using a RaySensor
#observations[constants.SENSOR_INDEX_TARGETING[0]] = int(self.target(agent) is not None)
# friends, foes = self.getFriendFoe(agent)
# if friends:
# # the 2 before that are the angle and heading to the center of mass of
# # the agent's team
# ax, ay = agent.state.position.x, agent.state.position.y
# cx, cy = self.get_friend_center(agent, friends)
# fd = self.distance((ax, ay), (cx, cy))
# ah = agent.state.rotation.z
# fh = self.angle((ax, ay, ah), (cx, cy)) + 180.0
# if fd <= constants.MAX_FRIEND_DISTANCE:
# observations[constants.SENSOR_INDEX_FRIEND_RADAR[0]] = fd / 15.0
# observations[constants.SENSOR_INDEX_FRIEND_RADAR[1]] = fh / 360.0
# The code above miscalculates the friend center by looking at all teammates
# instead of looking only inside the friend radius.
# Updated friend sensing code:
my_team = agent.get_team()
all_friends = self.teams[my_team]
ax, ay = agent.state.position.x, agent.state.position.y
cx, cy = 0.0, 0.0
if all_friends:
n = 0
for f in all_friends:
fx, fy = f.state.position.x, f.state.position.y
if self.distance((ax, ay), (fx, fy)) <= constants.MAX_FRIEND_DISTANCE:
n += 1
cx += fx
cy += fy
if n > 0:
cx, cy = cx / n, cy / n
fd = self.distance((ax, ay), (cx, cy))
ah = agent.state.rotation.z
fh = self.angle((ax, ay, ah), (cx, cy)) + 180.0
value = 1 - (fd / constants.MAX_FRIEND_DISTANCE)
value = max(0, min(value, 1))
observations[constants.SENSOR_INDEX_FRIEND_RADAR[0]] = value
observations[constants.SENSOR_INDEX_FRIEND_RADAR[1]] = fh / 360.0
if self.tracing:
if self.trace.initial_step is None:
self.trace.initial_step = agent.step
self.trace.position.append(agent.state.position)
self.trace.rotation.append(agent.state.rotation)
self.trace.sensors.append([o for o in observations])
from agent import KeyboardAgent
if self.tracing and isinstance(agent, KeyboardAgent):
id = common.addObject(
'data/shapes/cube/YellowCube.xml',
position = agent.state.position,
scale = OpenNero.Vector3f(0.25, 0.25, 0.25),
type = constants.OBJECT_TYPE_LEVEL_GEOM)
self.path_markers_trace.append(id)
return observations
def closure():
cam.setPosition(OpenNero.Vector3f(0, 0, 100))
cam.setTarget(OpenNero.Vector3f(100, 100, 0))
def setup_map(self):
"""
setup the test environment
"""
OpenNero.disable_ai()
if self.environment:
error("Environment already created")
return
# create the environment - this also creates the rtNEAT object
self.environment = self.create_environment()
OpenNero.set_environment(self.environment)
# world walls
height = constants.HEIGHT + constants.OFFSET
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM / 2, 0, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(1, constants.XDIM,
constants.HEIGHT),
label="World Wall0",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(0, constants.YDIM / 2, height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, constants.YDIM,
constants.HEIGHT),
label="World Wall1",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM, constants.YDIM / 2,
height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, constants.YDIM,
constants.HEIGHT),
label="World Wall2",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject("data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM / 2, constants.YDIM,
height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(1, constants.XDIM,
constants.HEIGHT),
label="World Wall3",
type=constants.OBJECT_TYPE_OBSTACLE)
# Add an obstacle wall in the middle
"""
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM/2, constants.YDIM/2, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(1, constants.YDIM / 4, constants.HEIGHT),
label="World Wall4",
type=constants.OBJECT_TYPE_OBSTACLE)
"""
# Add the surrounding Environment
common.addObject("data/terrain/NeroWorld.xml",
OpenNero.Vector3f(constants.XDIM / 2,
constants.YDIM / 2, 0),
scale=OpenNero.Vector3f(1, 1, 1),
label="NeroWorld",
type=constants.OBJECT_TYPE_LEVEL_GEOM)
self.spawnAgent(agent_xml='data/shapes/tree/Tree.xml',
first_person=False)
self.spawnAgent(agent_xml='data/shapes/character/steve_still_blue.xml',
first_person=False)
self.spawnAgent(agent_xml='data/shapes/character/sydney_still.xml',
first_person=False,
z_pos=5)
self.spawnAgent(agent_xml='data/shapes/cube/GreenCube.xml',
first_person=False,
z_pos=7)
return True
def __init__(self, xdim, ydim):
"""
Create the environment
"""
OpenNero.Environment.__init__(self)
self.XDIM = xdim
self.YDIM = ydim
self.max_steps = 500
self.states = {} # dictionary of agent states
self.crumbs = world_handler.pattern_cluster(500, "Roomba/world_config.txt")
# only keep crumbs that are inside the walls
self.crumbs = [c for c in self.crumbs if in_bounds(c.x,c.y)]
self.init_list = AgentInit()
self.init_list.add_type("<class 'Roomba.roomba.RoombaBrain'>")
self.init_list.add_type("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
#print self.init_list.types
roomba_abound = self.init_list.get_action("<class 'Roomba.roomba.RoombaBrain'>")
roomba_sbound = self.init_list.get_sensor("<class 'Roomba.roomba.RoombaBrain'>")
roomba_rbound = self.init_list.get_reward("<class 'Roomba.roomba.RoombaBrain'>")
rtneat_abound = self.init_list.get_action("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
rtneat_sbound = self.init_list.get_sensor("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
rtneat_rbound = self.init_list.get_reward("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
### Bounds for Roomba ###
# actions
roomba_abound.add_continuous(-math.pi, math.pi) # amount to turn by
# sensors
roomba_sbound.add_discrete(0,1) # wall bump
roomba_sbound.add_continuous(0,xdim) # self.x
roomba_sbound.add_continuous(0,ydim) # self.y
roomba_sbound.add_continuous(0,xdim) # closest.x
roomba_sbound.add_continuous(0,ydim) # closest.y
# rewards
roomba_rbound.add_continuous(-100,100) # range for reward
### End Bounds for Roomba ####
### Bounds for RTNEAT ###
# actions
rtneat_abound.add_continuous(-math.pi, math.pi) # amount to turn by
# sensors
rtneat_sbound.add_continuous(-1, 1)
rtneat_sbound.add_continuous(-1, 1)
rtneat_sbound.add_continuous(-1, 1)
rtneat_sbound.add_continuous(-1, 1)
rtneat_sbound.add_continuous(-1, 1)
rtneat_sbound.add_continuous(-1, 1)
# rewards
rtneat_rbound.add_continuous(-1, 1)
### End Bounds for RTNEAT ###
# set up shop
# Add Wayne's Roomba room with experimentally-derived vertical offset to match crumbs.
common.addObject("data/terrain/RoombaRoom.xml", OpenNero.Vector3f(xdim/2,ydim/2, -1), OpenNero.Vector3f(0,0,0), OpenNero.Vector3f(xdim/245.0, ydim/245.0, constants.HEIGHT/24.5), type = constants.OBJECT_TYPE_WALLS)
# OpenNero.getSimContext().addAxes()
self.add_crumbs()
for crumb in self.crumbs:
self.add_crumb_sensors(roomba_sbound)
def __init__(self, xdim, ydim, world_file = WORLD_FILE):
"""
Create the environment
"""
#self.Qlog = open("Qlog", "wb+")
OpenNero.Environment.__init__(self)
OpenNero.getSimContext().delay = 0.0;
self.XDIM = xdim
self.YDIM = ydim
self.max_steps = 500
self.states = {} # dictionary of agent states
if WORLD_FILE is None:
self.crumbs = world_handler.pattern_cluster(500, "Roomba/world_config.txt")
else: # read external file
data = world_handler.read_world(WORLD_FILE)
self.XDIM = data['dims'][0]
self.YDIM = data['dims'][1]
self.crumbs = data['pellets']
print len(self.crumbs)
# only keep crumbs that are inside the walls
self.crumbs = [c for c in self.crumbs if in_bounds(c.x,c.y)]
self.init_list = AgentInit()
self.init_list.add_type("<class 'Roomba.roomba.RoombaBrain'>")
self.init_list.add_type("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
self.init_list.add_type("<class 'Roomba.RLAgent.TabularRLAgent'>")
#print self.init_list.types
roomba_abound = self.init_list.get_action("<class 'Roomba.roomba.RoombaBrain'>")
roomba_sbound = self.init_list.get_sensor("<class 'Roomba.roomba.RoombaBrain'>")
roomba_rbound = self.init_list.get_reward("<class 'Roomba.roomba.RoombaBrain'>")
rtneat_abound = self.init_list.get_action("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
rtneat_sbound = self.init_list.get_sensor("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
rtneat_rbound = self.init_list.get_reward("<class 'Roomba.RTNEATAgent.RTNEATAgent'>")
### Bounds for Roomba ###
# actions
roomba_abound.add_continuous(-math.pi, math.pi) # amount to turn by
# sensors
roomba_sbound.add_discrete(0,1) # wall bump
roomba_sbound.add_continuous(0,xdim) # self.x
roomba_sbound.add_continuous(0,ydim) # self.y
roomba_sbound.add_continuous(0,xdim) # closest.x
roomba_sbound.add_continuous(0,ydim) # closest.y
# rewards
roomba_rbound.add_continuous(-100,100) # range for reward
### End Bounds for Roomba ####
### Bounds for RTNEAT ###
# actions
rtneat_abound.add_continuous(-math.pi, math.pi) # amount to turn by
#rtneat_abound.add_continuous(0, 1) # signal
# sensors
rtneat_sbound.add_continuous(-math.pi, math.pi) # nearest crumb angle
rtneat_sbound.add_continuous(0, 1) # proportion of crumb nearby
# angle and distance sensors for (up to) 8 nearest neighbors
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
rtneat_sbound.add_continuous(-math.pi, math.pi)
rtneat_sbound.add_continuous(0, 1)
# rewards
rtneat_rbound.add_continuous(-math.pi, math.pi)
### End Bounds for RTNEAT ###
#------------------------------------------------------------------------
rltabular_abound = self.init_list.get_action("<class 'Roomba.RLAgent.TabularRLAgent'>")
rltabular_sbound = self.init_list.get_sensor("<class 'Roomba.RLAgent.TabularRLAgent'>")
rltabular_rbound = self.init_list.get_reward("<class 'Roomba.RLAgent.TabularRLAgent'>")
### Bounds for RLTabular ###
# actions
rltabular_abound.add_continuous(-math.pi, math.pi) # amount to turn by
# sensors
rltabular_sbound.add_continuous(-1, 1)
rltabular_sbound.add_continuous(-1, 1)
rltabular_sbound.add_continuous(-1, 1)
rltabular_sbound.add_continuous(-1, 1)
rltabular_sbound.add_continuous(-1, 1)
rltabular_sbound.add_continuous(-1, 1)
# rewards
rltabular_rbound.add_continuous(-1, 1)
### End Bounds for RLTabular ###
#------------------------------------------------------------------------
# set up shop
# Add Wayne's Roomba room with experimentally-derived vertical offset to match crumbs.
common.addObject("data/terrain/RoombaRoom.xml", OpenNero.Vector3f(xdim/2,ydim/2, -1), OpenNero.Vector3f(0,0,0), OpenNero.Vector3f(xdim/245.0, ydim/245.0, constants.HEIGHT/24.5), type = constants.OBJECT_TYPE_WALLS)
# OpenNero.getSimContext().addAxes()
self.add_crumbs()
for crumb in self.crumbs:
self.add_crumb_sensors(roomba_sbound)
def setup(self):
# world walls
height = constants.HEIGHT + constants.OFFSET
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM/2, 0, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH, constants.XDIM, constants.HEIGHT*2),
label="World Wall0",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(0, constants.YDIM/2, height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(constants.WIDTH, constants.YDIM, constants.HEIGHT*2),
label="World Wall1",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM, constants.YDIM/2, height),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(constants.WIDTH, constants.YDIM, constants.HEIGHT*2),
label="World Wall2",
type=constants.OBJECT_TYPE_OBSTACLE)
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM/2, constants.YDIM, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH, constants.XDIM, constants.HEIGHT*2),
label="World Wall3",
type=constants.OBJECT_TYPE_OBSTACLE)
# Add an obstacle wall in the middle
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(constants.XDIM/2, constants.YDIM/2, height),
OpenNero.Vector3f(0, 0, 90),
scale=OpenNero.Vector3f(constants.WIDTH, constants.YDIM / 4, constants.HEIGHT*2),
label="World Wall4",
type=constants.OBJECT_TYPE_OBSTACLE)
# Add some trees
for i in (0.25, 0.75):
for j in (0.25, 0.75):
# don't collide with trees - they are over 500 triangles each
common.addObject(
"data/shapes/tree/Tree.xml",
OpenNero.Vector3f(i * constants.XDIM, j * constants.YDIM, constants.OFFSET),
OpenNero.Vector3f(0, 0, 0),
scale=OpenNero.Vector3f(1, 1, 1),
label="Tree %d %d" % (10 * i, 10 * j),
type=constants.OBJECT_TYPE_LEVEL_GEOM)
# collide with their trunks represented with cubes instead
common.addObject(
"data/shapes/cube/Cube.xml",
OpenNero.Vector3f(i * constants.XDIM, j * constants.YDIM, constants.OFFSET),
OpenNero.Vector3f(0,0,0),
scale=OpenNero.Vector3f(1,1,constants.HEIGHT),
type=constants.OBJECT_TYPE_OBSTACLE)
# Add the surrounding Environment
common.addObject(
"data/terrain/NeroWorld.xml",
OpenNero.Vector3f(constants.XDIM/2, constants.YDIM/2, 0),
scale=OpenNero.Vector3f(1.2, 1.2, 1.2),
label="NeroWorld",
type=constants.OBJECT_TYPE_LEVEL_GEOM)
