Introduction to the Modeling and Analysis of Complex Systems

450 CHAPTER 19. AGENT-BASED MODELSFor predator agents, the rules are somewhat opposite. If a predator agent can’t findany prey agent nearby, it dies with some probability because of the lack of food. But if itcan consume prey, it can also reproduce at a certain reproduction rate.Finally, both types of agents diffuse in space by random walk. The rates of diffusioncan be different between the two species, so let’s assume that predators can diffuse alittle faster than prey.The assumptions designed above can be implemented altogether in the update functionas follows. As you can see, the code is getting a bit longer than before, which reflectsthe increased complexity of the agents’ behavioral rules:Code 19.15:import copy as cpnr = 500. # carrying capacity of rabbitsmr = 0.03 # magnitude of movement of rabbitsdr = 1.0 # death rate of rabbits when it faces foxesrr = 0.1 # reproduction rate of rabbitsmf = 0.05 # magnitude of movement of foxesdf = 0.1 # death rate of foxes when there is no foodrf = 0.5 # reproduction rate of foxescd = 0.02 # radius for collision detectioncdsq = cd ** 2def 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)