def make_world(self, args):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world and set properties
world = World()
world.dimension_communication = 2
world.log_headers = [
"Agent_Type", "Fixed", "Perturbed", "X", "Y", "dX", "dY", "fX",
"fY", "Collision"
]
num_good_agents = 1
num_adversaries = 1
num_agents = num_adversaries + num_good_agents
num_landmarks = 0
# Add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.adversary = True if i < num_adversaries else False
agent.accel = 3.0 if agent.adversary else 4.0
# agent.accel = 20.0 if agent.adversary else 25.0
agent.collide = True
agent.silent = True
agent.size = 0.075 if agent.adversary else 0.05
agent.max_speed = 1.0 if agent.adversary else 1.3
# Add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.boundary = False
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
# Set perturbed policy agents
if args.perturbation:
self.adversaries(world)[
0].action_callback = double_pendulum_perturbation_strategy
self.adversaries(world)[0].is_perturbed_policy = True
# Add boundary landmarks
boundaries = [Landmark() for i in range(42)]
for i, bound in enumerate(boundaries):
bound.name = 'boundary {}'.format(i)
bound.boundary = True
bound.collide = True
bound.movable = False
bound.size = 3.0
world.landmarks = world.landmarks + boundaries
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args=None):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world and set properties
world = World()
world.dimension_communication = 2
num_adversaries = 1
num_agents = 3
num_landmarks = num_agents - 1
# Add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.adversary = True if i < num_adversaries else False
agent.collide = False
agent.silent = True
agent.size = 0.15
# Add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.collide = False
landmark.movable = False
landmark.size = 0.08
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args=None):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world
world = World()
# Add agents
world.agents = [Agent() for i in range(1)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.collide = False
agent.index = i
agent.silent = True
# Add landmarks
world.landmarks = [Landmark() for i in range(1)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.collide = False
landmark.index = i
landmark.movable = False
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args=None):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world and set properties
world = World()
world.collaborative = True
world.dimension_communication = 10
# Add agents
world.agents = [Agent() for i in range(2)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.collide = False
# Add landmarks
world.landmarks = [Landmark() for i in range(3)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.collide = False
landmark.movable = False
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world and set properties
world = World()
world.dimension_communication = 2
world.log_headers = [
"Agent_Type", "Fixed", "Perturbed", "X", "Y", "dX", "dY", "fX",
"fY", "Collision"
]
num_good_agents = 3
num_adversaries = 2
num_fixed_adv = 0
num_agents = num_adversaries + num_good_agents
num_landmarks = 1
# Add adversarial agents
world.agents = [Agent() for i in range(num_adversaries)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.accel = 3.0
# agent.accel = 20.0
agent.adversary = True
agent.collide = True
agent.silent = True
agent.size = 0.05
agent.max_speed = 1.0
# Add fixed policy sheep agents
fixed_agents = [Agent() for i in range(num_good_agents)]
for i, fixed in enumerate(fixed_agents):
fixed.name = 'agent {}'.format(num_adversaries + i)
fixed.accel = 5.0
fixed.action_callback = sheep_fixed_strategy
fixed.adversary = False
fixed.collide = True
fixed.is_fixed_policy = True
fixed.max_speed = 0.5
fixed.silent = True
fixed.size = 0.025
world.agents += fixed_agents
# Add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.boundary = False
landmark.collide = False
landmark.movable = False
landmark.size = 0.1
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Debug verbose output
self.debug = False
# Create world and set properties
world = World()
world.dimension_communication = 2
world.log_headers = [
"Agent_Type", "Fixed", "Perturbed", "X", "Y", "dX", "dY", "fX",
"fY", "Collision"
]
# Defender and Attacker
num_agents = 2
# High Value Target (HVT)
num_landmarks = 1
# Add agents
world.agents = [Agent() for i in range(num_agents)]
# All agents and the HVT have the same base size
# size is in mm?
factor = 0.25
size = 0.025 * factor
# Standard
attacker_size = 5 * size
attacker_sense_region_size = size * (20 / factor)
defender_size = size
defender_sense_region_size = size * (4 / factor)
hvt_size = size + defender_sense_region_size
hvt_sense_region_size = size * (20 / factor)
# 50% of the HVT size
defender_size = hvt_size * 0.5
hvt_size *= 2
hvt_sense_region_size = hvt_size
# Attacker
world.agents[0].name = 'agent {}'.format(1)
world.agents[0].adversary = True
world.agents[0].accel = 3.0
world.agents[0].collide = True
world.agents[0].color = np.array([0.85, 0.35, 0.35])
world.agents[0].has_sense = True
world.agents[0].silent = True
world.agents[0].sense_region = attacker_sense_region_size
world.agents[0].size = attacker_size
world.agents[0].max_speed = 1.0
# Defender
# Sense region for defender is 20% smaller because
# it has a speed advantage over the attacker
world.agents[1].name = 'agent {}'.format(0)
world.agents[1].accel = 4.0
world.agents[1].collide = True
world.agents[1].color = np.array([0.35, 0.85, 0.35])
world.agents[1].has_sense = True
world.agents[1].sense_region = 0.1
world.agents[1].silent = True
world.agents[1].sense_region = defender_sense_region_size
world.agents[1].size = defender_size
world.agents[1].max_speed = 1.3
# Add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
# High Value Target (HVT)
# Sense region for HVT is 20% larger because it cannot move
world.landmarks[0].name = 'landmark {}'.format(0)
world.landmarks[0].boundary = False
world.landmarks[0].collide = False
world.landmarks[0].color = np.array([0.25, 0.25, 0.25])
world.landmarks[0].has_sense = True
world.landmarks[0].movable = False
world.landmarks[0].sense_region = hvt_sense_region_size
world.landmarks[0].size = hvt_size
# Add boundary landmarks
world.landmarks = world.landmarks + world.set_dense_boundaries()
# Make initial conditions
self.reset_world(world)
return world
def make_world(self, args=None):
"""
Construct the world
Returns:
world (multiagent_particle_env.core.World): World object with agents and landmarks
"""
# Create world and set properties
world = World()
# world.damping = 1
world.dimension_communication = 4
num_good_agents = 2
num_adversaries = 4
num_agents = num_adversaries + num_good_agents
num_landmarks = 1
num_food = 2
num_forests = 2
# Add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent {}'.format(i)
agent.adversary = True if i < num_adversaries else False
agent.accel = 3.0 if agent.adversary else 4.0
# agent.accel = 20.0 if agent.adversary else 25.0
agent.collide = True
agent.leader = True if i == 0 else False
agent.max_speed = 1.0 if agent.adversary else 1.3
agent.silent = True if i > 0 else False
agent.size = 0.075 if agent.adversary else 0.045
# Add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark {}'.format(i)
landmark.boundary = False
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
# Add food landmarks
world.food = [Landmark() for i in range(num_food)]
for i, landmark in enumerate(world.food):
landmark.name = 'food {}'.format(i)
landmark.boundary = False
landmark.collide = False
landmark.movable = False
landmark.size = 0.03
world.landmarks += world.food
# Add forest landmarks
world.forests = [Landmark() for i in range(num_forests)]
for i, landmark in enumerate(world.forests):
landmark.name = 'forest {}'.format(i)
landmark.boundary = False
landmark.collide = False
landmark.movable = False
landmark.size = 0.3
world.landmarks += world.forests
# World boundaries now penalized with negative reward
# world.landmarks += world.set_boundaries()
# Make initial conditions
self.reset_world(world)
return world