11.7. Implementing Sugarscape

Sugarscape is more complicated than the previous models, so we won’t present the entire implementation here. we will outline the structure of the code and you can see the details in the Jupyter notebook for this chapter, chap11.ipynb, which is in the repository for this book. If you are not interested in the details, you can skip this section.

During each step, the agent moves, harvests sugar, and ages. Here is the Agent class and its step method:

class Agent:

    def step(self, env):
        self.loc = env.look_and_move(self.loc, self.vision)
        self.sugar += env.harvest(self.loc) - self.metabolism
        self.age += 1

The parameter env is a reference to the environment, which is a Sugarscape object. It provides methods look_and_move and harvest:

Sugarscape inherits from Cell2D, so it is similar to the other grid-based models we’ve seen.

The attributes include agents, which is a list of Agent objects, and occupied, which is a set of tuples, where each tuple contains the coordinates of a cell occupied by an agent.

Here is the Sugarscape class and its step method:

class Sugarscape(Cell2D):

    def step(self):

        # loop through the agents in random order
        random_order = np.random.permutation(self.agents)
        for agent in random_order:

            # mark the current cell unoccupied

            # execute one step

            # if the agent is dead, remove from the list
            if agent.is_starving():
                # otherwise mark its cell occupied

        # grow back some sugar
        return len(self.agents)

During each step, the Sugarscape uses the NumPy function permutation so it loops through the agents in random order. It invokes step on each agent and then checks whether it is dead. After all agents have moved, some of the sugar grows back. The return value is the number of agents still alive.

I won’t show more details here; you can see them in the notebook for this chapter. If you want to learn more about NumPy, you might want to look at these functions in particular:

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