def __init__(self, name, model):
"""Initialize the agent."""
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.carryable = False
# Define a BTContruct object
self.bt = BTConstruct(None, self)
self.shared_content = dict()
self.food_collected = 0
self.bt.xmlstring = model.xmlstring
self.bt.construct()
# self.diversity_fitness = model.fitness
# Location history
self.location_history = set()
self.timestamp = 0
self.step_count = 0
def __init__(self, name, model, xmlstring=None):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.moveable = True
self.shared_content = dict()
self.carryable = False
# Define a BTContruct object
self.bt = BTConstruct(None, self)
class DummyIndividual:
def __init__(self):
self.phenotype = None
dummyind = DummyIndividual()
self.individual = [dummyind]
self.individual[0].phenotype = xmlstring
self.bt.xmlstring = xmlstring
self.bt.construct()
"""
def gen_from_xmlstring():
"""Generate BT graph from xml string."""
dname = '/home/aadeshnpn/Documents/BYU/hcmi/hri/supporting_materials/nest_maintenance' # noqa: E501
xmlstring = ''
m = Model()
a = Agent('1', m)
bt = BTConstruct(None, a, xmlstring)
bt.construct()
bt.visualize(name=dname + '/' + str(90))
def __init__(self, name, model):
"""Initialize the agent."""
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.results = "db" # This can take 2 values. db or file
# self.exchange_time = model.random.randint(2, 4)
# This doesn't help. Maybe only perform genetic operations when
# an agents meet 10% of its total population
# """
self.operation_threshold = 2
self.genome_storage = []
# Define a BTContruct object
self.bt = BTConstruct(None, self)
# self.blackboard = Blackboard()
# self.blackboard.shared_content = dict()
self.shared_content = dict()
# self.shared_content = dict(
self.carryable = False
self.beta = 0.0001
self.food_collected = 0
# Grammatical Evolution part
from ponyge.algorithm.parameters import Parameters
parameter = Parameters()
parameter_list = ['--parameters', '../..,' + model.parm]
# Comment when different results is desired.
# Else set this for testing purpose
# parameter.params['RANDOM_SEED'] = name
# # np.random.randint(1, 99999999)
parameter.params['POPULATION_SIZE'] = self.operation_threshold // 2
parameter.set_params(parameter_list)
self.parameter = parameter
individual = initialisation(self.parameter, 1)
individual = evaluate_fitness(individual, self.parameter)
self.individual = individual
self.bt.xmlstring = self.individual[0].phenotype
self.bt.construct()
self.diversity_fitness = self.individual[0].fitness
self.delayed_reward = 0
# Location history
self.location_history = set()
self.timestamp = 0
self.step_count = 0
self.fitness_name = True
def main():
"""Parse args and call bt visualize module."""
# dname = '/home/aadeshnpn/Documents/BYU/hcmi/hri/supporting_materials/nest_maintenance' # noqa: E501
# jfname = dname + '/1539014820252.json'
# dname = '/home/aadeshnpn/Documents/BYU/hcmi/hri/supporting_materials/cooperative_transport' # noqa: E501
# jfname = dname + '/1538447335350.json'
dname = '/home/aadeshnpn/Documents/BYU/hcmi/hri/supporting_materials/foraging' # noqa: E501
jfname = dname + '/1538473090382007.json'
jdata = JsonPhenotypeData.load_json_file(jfname)
phenotypes = jdata['phenotypes']
for i in range(len(phenotypes)):
# if i >= 5:
# break
m = Model()
a = Agent('1', m)
bt = BTConstruct(None, a, phenotypes[i])
bt.construct()
bt.visualize(name=dname + '/' + str(i))
def __init__(self, name, model):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
# self.exchange_time = model.random.randint(2, 4)
# This doesn't help. Maybe only perform genetic operations when
# an agents meet 10% of its total population
# """
self.operation_threshold = 2
self.genome_storage = []
# Define a BTContruct object
self.bt = BTConstruct(None, self)
self.blackboard = Blackboard()
self.blackboard.shared_content = dict()
self.shared_content = dict()
# Grammatical Evolution part
from ponyge.algorithm.parameters import Parameters
parameter = Parameters()
parameter_list = ['--parameters', 'swarm.txt']
# Comment when different results is desired.
# Else set this for testing purpose
parameter.params['RANDOM_SEED'] = name
# np.random.randint(1, 99999999)
parameter.params['POPULATION_SIZE'] = self.operation_threshold // 2
parameter.set_params(parameter_list)
self.parameter = parameter
individual = initialisation(self.parameter, 1)
individual = evaluate_fitness(individual, self.parameter)
self.individual = individual
self.bt.xmlstring = self.individual[0].phenotype
self.bt.construct()
def __init__(self, name, model):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.operation_threshold = 2
self.genome_storage = []
# Define a BTContruct object
self.bt = BTConstruct(None, self)
self.blackboard = Blackboard()
self.blackboard.shared_content = dict()
# Grammatical Evolution part
from ponyge.algorithm.parameters import Parameters
parameter = Parameters()
parameter_list = ['--parameters', 'swarm.txt']
parameter.params['POPULATION_SIZE'] = self.operation_threshold // 2
parameter.params['RANDOM_SEED'] = model.seed
parameter.set_params(parameter_list)
self.parameter = parameter
individual = initialisation(self.parameter, 1)
self.individual = individual
self.bt.xmlstring = self.individual[0].phenotype
self.bt.construct()
self.output = py_trees.display.ascii_tree(self.bt.behaviour_tree.root)
# Location history
self.location_history = set()
self.timestamp = 0
def __init__(self, name, model):
"""Initialize the agent."""
super().__init__(name, model)
self.location = ()
# Agent attributes for motion
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.carryable = False
self.shared_content = dict()
self.debris_collected = 0
# Results
self.results = "db" # This can take 2 values. db or file
# Behavior Tree Class
self.bt = BTConstruct(None, self)
# Location history
self.location_history = set()
# Step count
self.timestamp = 0
self.step_count = 0
self.fitness_name = True
def __init__(self, name, model, xmlstring=None, prob=0.5):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.moveable = True
self.shared_content = dict()
self.prob = prob
self.carryable = False
# Define a BTContruct object
self.bt = BTConstruct(None, self)
class DummyIndividual:
def __init__(self):
self.phenotype = None
dummyind = DummyIndividual()
self.individual = [dummyind]
self.individual[0].phenotype = xmlstring
self.bt.xmlstring = xmlstring
self.bt.construct()
# When the actuator is not working. We repalce the move
# premitive behavior with dummpy move behaviors 50% of
# the time.
self.dummy_bt = self.replace_nodes()
# Move node only works 50% of the time
# py_trees.logging.level = py_trees.logging.Level.DEBUG
# py_trees.display.print_ascii_tree(self.dummy_bt.behaviour_tree.root)
"""
def __init__(self, name, model, xmlstring=None):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.moveable = True
self.shared_content = dict()
self.carryable = False
# Define a BTContruct object
self.bt = BTConstruct(None, self)
class DummyIndividual:
def __init__(self):
self.phenotype = None
dummyind = DummyIndividual()
self.individual = [dummyind]
self.individual[0].phenotype = xmlstring
# self.bt.xmlstring = xmlstring
# self.bt.construct()
# Drop branch
dseq = py_trees.composites.Sequence('DSequence')
iscarrying = IsCarrying('IsCarrying_Food')
iscarrying.setup(0, self, 'Food')
neighhub = NeighbourObjects('NeighbourObjects_Hub')
neighhub.setup(0, self, 'Hub')
notneighhub = py_trees.meta.inverter(NeighbourObjects)(
'NeighbourObjects_Hub')
notneighhub.setup(0, self, 'Hub')
drop = CompositeDrop('CompositeDrop_Food')
drop.setup(0, self, 'Food')
dseq.add_children([neighhub, drop])
# Carry branch
cseq = py_trees.composites.Sequence('CSequence')
neighsite = NeighbourObjects('NeighbourObjects_Sites')
neighsite.setup(0, self, 'Sites')
neighfood = NeighbourObjects('NeighbourObjects_Food')
neighfood.setup(0, self, 'Food')
invcarrying = py_trees.meta.inverter(IsCarrying)('IsCarrying_Food')
invcarrying.setup(0, self, 'Food')
carry = CompositeSingleCarry('CompositeSingleCarry_Food')
carry.setup(0, self, 'Food')
cseq.add_children([neighsite, neighfood, invcarrying, carry])
# Locomotion branch
# Move to site
siteseq = py_trees.composites.Sequence('SiteSeq')
sitefound = IsVisitedBefore('IsVisitedBefore_Sites')
sitefound.setup(0, self, 'Sites')
gotosite = MoveTowards('MoveTowards_Sites')
gotosite.setup(0, self, 'Sites')
siteseq.add_children([sitefound, invcarrying, gotosite])
# siteseq.add_children([invcarrying])
# Move to hub
hubseq = py_trees.composites.Sequence('HubSeq')
gotohub = MoveTowards('MoveTowards_Hub')
gotohub.setup(0, self, 'Hub')
hubseq.add_children([iscarrying, gotohub])
sitenotfound = py_trees.meta.inverter(IsVisitedBefore)(
'IsVisitedBefore_Sites')
sitenotfound.setup(0, self, 'Sites')
explore = Explore('Explore')
explore.setup(0, self)
randwalk = py_trees.composites.Sequence('Randwalk')
randwalk.add_children([sitenotfound, explore])
locoselect = py_trees.composites.Selector('Move')
# locoselect.add_children([siteseq, hubseq, explore])
locoselect.add_children([hubseq, randwalk])
select = py_trees.composites.Selector('Main')
select.add_children([dseq, cseq, locoselect])
self.behaviour_tree = py_trees.trees.BehaviourTree(select)
py_trees.display.render_dot_tree(self.behaviour_tree.root,
name=model.pname + '/forgehc')
def __init__(self, name, model, xmlstring=None):
super().__init__(name, model)
self.location = ()
self.direction = model.random.rand() * (2 * np.pi)
self.speed = 2
self.radius = 3
self.moveable = True
self.shared_content = dict()
self.carryable = False
# Define a BTContruct object
self.bt = BTConstruct(None, self)
class DummyIndividual:
def __init__(self):
self.phenotype = None
dummyind = DummyIndividual()
self.individual = [dummyind]
self.individual[0].phenotype = xmlstring
# self.bt.xmlstring = xmlstring
# self.bt.construct()
# self.shared_content['Hub'] = {model.hub}
# self.shared_content['Sites'] = {model.site}
# Drop branch
dseq = py_trees.composites.Sequence('DSequence')
iscarrying = IsInPartialAttached('IsInPartialAttached_Food')
iscarrying.setup(0, self, 'Food')
# If near hub and carrying food with other agents drop
neighhub = NeighbourObjects('NeighbourObjects_Hub')
neighhub.setup(0, self, 'Hub')
drop = CompositeDropPartial('CompositeDropPartial_Food')
drop.setup(0, self, 'Food')
dseq.add_children([neighhub, drop])
# Carry branch
cseq = py_trees.composites.Sequence('CSequence')
# neighsite = NeighbourObjects('5')
# neighsite.setup(0, self, 'Sites')
neighhub = py_trees.meta.inverter(NeighbourObjects)(
'NeighbourObjects_Hub')
neighhub.setup(0, self, 'Hub')
neighfood = NeighbourObjects('NeighbourObjects_Food')
neighfood.setup(0, self, 'Food')
invcarrying = py_trees.meta.inverter(IsInPartialAttached)(
'IsInPartialAttached_Food')
invcarrying.setup(0, self, 'Food')
carry = CompositeMultipleCarry('CompositeMultipleCarry_Food')
carry.setup(0, self, 'Food')
# Move to hub
hubseq = py_trees.composites.Sequence('HubSeq')
# If carrying something to go to hub
gotohub = MoveTowards('MoveTowards_Hub')
gotohub.setup(0, self, 'Hub')
hubseq.add_children([iscarrying, gotohub])
cseq.add_children([neighhub, neighfood, carry, hubseq])
# Locomotion branch
# Move to site
siteseq = py_trees.composites.Sequence('SiteSeq')
# If site already found and not carrying anything go to site
sitefound = IsVisitedBefore('IsVisitedBefore_Sites')
sitefound.setup(0, self, 'Sites')
gotosite = MoveTowards('MoveTowards_Sites')
gotosite.setup(0, self, 'Sites')
siteseq.add_children([sitefound, invcarrying, gotosite])
# Do Random walk
explore = Explore('Explore')
explore.setup(0, self)
randwalk = py_trees.composites.Sequence('Randwalk')
randwalk.add_children([explore])
# Try to got to site and hub if not explore
locoselect = py_trees.composites.Selector('Move')
locoselect.add_children([iscarrying, siteseq, explore])
# First try to drop then collect or explore
select = py_trees.composites.Selector('Main')
select.add_children([dseq, cseq, locoselect])
self.behaviour_tree = py_trees.trees.BehaviourTree(select)
py_trees.display.render_dot_tree(self.behaviour_tree.root,
name=model.pname + '/cthc')