Introduction to the Modeling and Analysis of Complex Systems

454 CHAPTER 19. AGENT-BASED MODELSfoxes = [ag for ag in agents if ag.type == ’f’]if len(foxes) > 0:x = [ag.x for ag in foxes]y = [ag.y for ag in foxes]plot(x, y, ’ro’)axis(’image’)axis([0, 1, 0, 1])def update():global agentsif agents == []:returnag = agents[randint(len(agents))]# simulating random movementm = mr if ag.type == ’r’ else mfag.x += uniform(-m, m)ag.y += uniform(-m, m)ag.x = 1 if ag.x > 1 else 0 if ag.x < 0 else ag.xag.y = 1 if ag.y > 1 else 0 if ag.y < 0 else ag.y# detecting collision and simulating death or birthneighbors = [nb for nb in agents if nb.type != ag.typeand (ag.x - nb.x)**2 + (ag.y - nb.y)**2 < cdsq]if ag.type == ’r’:if len(neighbors) > 0: # if there are foxes nearbyif random() < dr:agents.remove(ag)returnif random() < rr*(1-sum(1 for x in agents if x.type == ’r’)/nr):agents.append(cp.copy(ag))else:if len(neighbors) == 0: # if there are no rabbits nearbyif random() < df:agents.remove(ag)