Initializing Agents


All HASH simulations begin life in the init file found in the root of a HASH project. In this file we generate the starting state, or initial conditions of the simulated world.

There are three ways to populate the initial state of a simulation. You can:

  1. Define the individual agents in init.json
  2. Define "creator" agents in init.json with behaviors that will generate agents
  3. Programmatically generate the initial agents directly in an init.js or init.py file.

init.json

In init.json you'll explicitly define all your agents as JSON blobs in an array. Here's what that might look like:

Defining five agents in init.json

You can create whatever field names you need on your agents, but be aware of setting incorrect value types on protected fields we mentioned previously.

init.json

[
    {"position": [0,0],
     "behaviors": ["foo.js"]},
    {"position": [0,0],
     "behaviors": ["foo.js"]},
]

When you make a change to the file, you'll need to reset your simulation to see updated agents appear in the 3D Viewer.

init.js and init.py

The default init.json approach has some limitations. Because it's compliant JSON, you can't set dynamically set properties on the agent. If you want to generate random values, or run loops to generate your agents, then init.js or init.py will give you that functionality.

You can transform the init.json file into a JavaScript or Python file by right clicking it and selecting "Convert to..." your desired language.

When you do, any defined agents will be added as objects in an array named agents.

Now you can write JavaScript or Python in the file and use it to set agent properties.

JavaScript
Python
const init = (context) => {
  let agents = [
    {
      position: [0, 0],
      behaviors: ["custom.js"],
      foo: Math.random(),
      data: context.data()["/somedataset"][1],
    },
  ];

  return agents;
};

init.js and init.py must return an array of objects

To programmatically create agents, you can add loops and similar logic to append agents to the array.

JavaScript
Python
const init = (context) => {
  let agents = [];
  for (let i = 0; i < 100; i++) {
    agents.push({
      position: [i, i],
    });
  }
  return agents;
};

Within an init.js or init.py file you have access to the context of the simulation, where you can access the data and global variables attached to the simulation. You can use them to seed values in your initialization.

JavaScript
Python
/**
 * @param {InitContext} initialization context
 */
const init = (context) => {
  const data = context.data();
  const globals = context.globals();

  let avg_age = hstd.stats.mean(data["ages.json"]);
  let std_age = hstd.stats.stdev(data["ages.json"]);

  let agents = [];
  for (let i = 0; i < globals["num_agents"]; i++) {
    agents.push({
      behaviors: ["add_one.js"],
      age: Math.floor(hstd.stats.normal.sample(avg_age, std_age)),
    });
  }

  return agents;
};

The context object in the init file is slightly different from the context available during a simulation run. Neighbors and messages won't be available as they don't exist before a simulation starts.

You can also make use of functions in HASH's standard library to generate agents in predefined patterns.

const init = (context) => {
  const topology = context.globals().topology;
  const template = {
    behaviors: ["grow.js"],
    color: "yellow",
  };

  const agents = hstd.init.grid(topology, template);
  return agents;
};

You can learn more about all the init functions in the standard library in this section of the docs.

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