""" agent.py - Part of ants project This model implements the actual agents on the grid (a.k.a. the ants) License: AGPL 3 (see end of file) (C) Alexander Bocken, Viviane Fahrni, Grace Kragho """ import numpy as np from mesa.agent import Agent from mesa.space import Coordinate from typing import overload class RandomWalkerAnt(Agent): def __init__(self, unique_id, model, look_for_chemical=None, energy_0=1, chemical_drop_rate_0=1, sensitvity_0=1, alpha=0.5) -> None: super().__init__(unique_id=unique_id, model=model) self._next_pos : None | Coordinate = None self.prev_pos : None | Coordinate = None self.look_for_chemical = look_for_chemical self.drop_chemical = None self.energy : float = energy_0 self.sensitvity : float = sensitvity_0 self.chemical_drop_rate : float = chemical_drop_rate_0 #TODO: check whether needs to be separated into A and B self.alpha = alpha def sensitvity_to_concentration(self, prop : float) -> float: # TODO return prop def step(self): # follow positive gradient if self.look_for_chemical is not None: front_concentration = [self.model.grid.fields[self.look_for_chemical][cell] for cell in self.front_neighbors ] gradient = front_concentration - np.repeat(self.model.grid.fields[self.look_for_chemical][self.pos], 3) index = np.argmax(gradient) if gradient[index] > 0: self._next_pos = self.front_neighbors[index] return # do biased random walk p = np.random.uniform() if p < self.alpha: self._next_pos = self.front_neighbor else: # need copy() as we would otherwise remove the tuple from all possible lists (aka python "magic") other_neighbors = self.neighbors().copy() other_neighbors.remove(self.front_neighbor) random_index = np.random.choice(range(len(other_neighbors))) self._next_pos = other_neighbors[random_index] def drop_chemicals(self) -> None: # should only be called in advance() as we do not use hidden fields if self.drop_chemical is not None: self.model.grid.fields[self.drop_chemical][self.pos] += self.chemical_drop_rate def advance(self) -> None: self.drop_chemicals() self.prev_pos = self.pos self.pos = self._next_pos # TODO: find out how to decorate with property properly def neighbors(self, pos=None, include_center=False): if pos is None: pos = self.pos return self.model.grid.get_neighborhood(pos, include_center=include_center) @property def front_neighbors(self): """ returns all three neighbors which the ant can see """ assert(self.prev_pos is not None) all_neighbors = self.neighbors() neighbors_at_the_back = self.neighbors(pos=self.prev_pos, include_center=True) return list(filter(lambda i: i not in neighbors_at_the_back, all_neighbors)) @property def front_neighbor(self): """ returns neighbor of current pos which is towards the front of the ant """ neighbors_prev_pos = self.neighbors(self.prev_pos) for candidate in self.front_neighbors: # neighbor in front direction only shares current pos as neighborhood with prev_pos candidate_neighbors = self.model.grid.get_neighborhood(candidate) overlap = [x for x in candidate_neighbors if x in neighbors_prev_pos] if len(overlap) == 1: return candidate """ This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details. You should have received a copy of the GNU Affero General Public License along with this program. If not, see """