def __init__(
self,
name="",
host=None,
serializer=None,
transport=None,
attributes=None,
backend=Backend.OSBRAIN,
mesa_model=None,
):
self.backend = self.validate_backend(backend)
if self.backend == Backend.OSBRAIN:
self._remove_methods(MesaAgent)
osBrainAgent.__init__(
self,
name=name,
host=host,
serializer=serializer,
transport=transport,
attributes=attributes,
)
elif self.backend == Backend.MESA:
MesaAgent.__init__(self, name, mesa_model)
self._remove_methods(osBrainAgent)
self.init_mesa(name)
self.unique_id = name
self.name = name
self.mesa_model = mesa_model
def __init__(self, pos, model, init_state=DEAD):
'''
Create a cell, in the given state, at the given x, y position.
'''
Agent.__init__(self, pos, model)
self.x, self.y = pos
self.state = init_state
self._nextState = None
def __init__(self, unique_id, model, fsm_size, num_tokens):
Agent.__init__(self, unique_id, model)
self.state = 0
self.unique_id = unique_id
self.scores = []
self.decision = NO_ACTION
self.gen_automata(fsm_size, num_tokens)
def __init__(self, pos, model, initial_state):
'''
Create a cell, in the given state, at the given row, col position.
'''
Agent.__init__(self, pos, model)
self._row = pos[1]
self._col = pos[0]
self._state = initial_state
self._next_state = None
def __init__(self, pos, model, init_state):
'''
Create a cell, in the given state, at the given x, y position.
'''
Agent.__init__(self, pos, model)
self._x = pos[0]
self._y = pos[1]
self._state = init_state
self._nextState = None
def __init__(self, pos, model, initial_state):
'''
Create a cell, in the given state, at the given row, col position.
'''
Agent.__init__(self, pos, model)
self._row = pos[1]
self._col = pos[0]
self._state = initial_state
self._next_state = None
def __init__(self, intersection, model):
unique_id = uuid4()
Agent.__init__(self, unique_id, model)
Intersection.__init__(
self,
intersection.name,
intersection.geometry,
intersection.input_links,
intersection.output_links,
)
def __init__(self, unique_id, model, homeLoc, workLoc):
Agent.__init__(self, unique_id, model)
self.age = random.randint(18, 87)
degredation_age = 37
max_age = 100
# self.ability = random.random()**4 * (((min(abs((max_age+degredation_age)-self.age)),max_age))/max_age) #based on formula A_b on pg. 354
self.ability = 1
self.attitude = random.random()**3 # based on A_t on pg. 354
self.home = homeLoc
self.work = workLoc
def __init__(self, id, model, params):
Agent.__init__(self, id, model)
student_params= {
'join_chat_prob': 0.15,
'join_board_prob': 0.15,
'post_prob': 0.3,
'reduced_post_prob': 0.1,
'chat_social_prob': 0.5,
'post_social_prob': 0.1,
'discount': 0.95
}
student_params.update(params)
self.in_chat = False
self.in_board = False
self.engaged = False
self.chats_read = 0
self.chats_social_read = 0
self.overload_chats_read = 0
self.overload_chats_social_read = 0
self.contrib_chat = 0
self.contrib_social_chat = 0
self.at_post = 0
self.at_social_post = 0
self.posts_read = 0
self.posts_social_read = 0
self.overload_posts_read = 0
self.overload_posts_social_read = 0
self.contrib_post = 0
self.contrib_social_post = 0
self.join_chat_prob = student_params['join_chat_prob']
self.join_board_prob = student_params['join_board_prob']
self.post_prob = student_params['post_prob']
self.reduced_post_prob = student_params['reduced_post_prob']
self.chat_social_prob = student_params['chat_social_prob']
self.post_social_prob = student_params['post_social_prob']
self.discount = student_params['discount']
self.post_overload_lim = 50
self.chat_overload_lim = 50
self.post_overloaded = False
self.chat_overloaded = False
def __init__(self, unique_id, model, belief, age=18):
Agent.__init__(self, unique_id, model)
self.unique_id = unique_id
self.belief = belief
self.age = age
self.pro_friend = 0
self.anti_friend = 0
self.none = 0
self.num_rounds = 0
if self.age <= 19:
self.prob_ref = 0
elif self.age <= 24:
self.prob_ref = 1
elif self.age <= 29:
self.prob_ref = 2
else:
self.prob_ref = 3
def __init__(self, id, model=None):
Agent.__init__( self, id, model)
#_configure_logging()
self.l = logging.getLogger(self.__class__.__name__)
self._xd = XMLObject('Agent')
self._meta = self._xd.add("metadata")
self._meta.el.set("id", str(id))
self._events = self._xd.add("events")
self._envdata = self._xd.add("environments")
self._body = self._xd.add("body")
self._behaviours = []
self._sensors = [Sensor()]
self._next_reward = 0.0
self._last_reward = 0.0
self.avStates = []
self.avActions = []
self.exists = False
self._brain = BaseBrain(self)
self.pos = (0,0)
def __init__(self, unique_id, model, intitial_state):
Agent.__init__(self, unique_id, model)
self.belief = intitial_state
def __init__(self, pos, model, energy):
Agent.__init__(self, pos, model)
EnergyConsumingEntity.__init__(self, energy)
def __init__(self, unique_id, model):
Agent.__init__(self, unique_id, model)
self.wealth = 1
def __init__(self, pos, model, age=0):
Agent.__init__(self, pos, model)
AgingEntity.__init__(self, age)
