13.5. Simulation

Now that we have agents and a fitness landscape, we will define a class called Simulation that simulates the creation, reproduction, and death of the agents. To avoid getting bogged down, we will see a simplified version of the code here; you can see the details in the notebook for this chapter.

Here’s the definition of Simulation:

class Simulation:

    def __init__(self, fit_land, agents):
        self.fit_land = fit_land
        self.agents = agents

The attributes of a Simulation are:

• fit_land: A reference to a FitnessLandscape object.

• agents: An array of Agent objects.

The most important function in Simulation is step, which simulates one time step:

# class Simulation:

    def step(self):
        n = len(self.agents)
        fits = self.get_fitnesses()

        # see who dies
        index_dead = self.choose_dead(fits)
        num_dead = len(index_dead)

        # replace the dead with copies of the living
        replacements = self.choose_replacements(num_dead, fits)
        self.agents[index_dead] = replacements

step uses three other methods:

• get_fitnesses: returns an array containing the fitness of each agent.

• choose_dead: decides which agents die during this time step, and returns an array that contains the indices of the dead agents.

• choose_replacements: decides which agents reproduce during this time step, invokes copy on each one, and returns an array of new Agent objects.

In this version of the simulation, the number of new agents during each time step equals the number of dead agents, so the number of live agents is constant.

Q-1: What happens when an agent dies in this version of the simulation?

• If an agent dies then a new agent will be made in the next time step so the amount of agents is always changing.
• Sorry but when one agent dies another is made within that same time step so the amount of agents is constant.
• If an agent dies no new agent will take its place leading to all the agents being dead eventually.
• Sorry but a new agent will be made to replace an agent if it dies.
• If an agent dies then a new agent is made within that same time step so that the number of live agents is constant.
• Correct!
• None of the above.
• Incorrect. There is one correct answer.

Q-2:
• fit_land
• A reference to a FitnessLandscape object.
• agents
• An array of Agent objects.
• git_fitnesses
• Returns an array containing the fitness of each agent.
• choose_dead
• Decides which agents die during this time step, and returns an array that contains the indices of the dead agents.
• choose_replacements
• Decides which agents reproduce during this time step, invokes copy on each one, and returns an array of new Agent objects.

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