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, 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)