Simulate Complex Systems with HASH: A Step-by-Step Guide

Introduction

When you're trying to understand how the world works, simple math sometimes does the trick. For instance, increasing hot water flow by X raises temperature by Y. But many real-world systems are too tangled for such neat formulas. Think of a warehouse where adding a fifth worker actually cuts efficiency because they get in each other's way. You can't predict that with a linear equation—but you can simulate it. That's where HASH, a free online platform, comes in. HASH lets you write short JavaScript snippets that model individual agents (workers, customers, or anything else) and then watch the system unfold. You can tweak parameters, test rules, and gain deep insights into complex problems. This guide will walk you through creating your first simulation, turning vague hunches into measurable outcomes.

Simulate Complex Systems with HASH: A Step-by-Step Guide — Source: www.joelonsoftware.com

What You'll Need

A modern web browser (Chrome, Firefox, Edge, or Safari)
A free HASH account (sign up at hash.ai)
Basic familiarity with JavaScript (optional but helpful)
A specific problem you want to model (e.g., warehouse workflow, traffic flow, or ecosystem dynamics)

Step 1: Sign Up and Explore the Dashboard

Navigate to hash.ai and click Get Started. Create your free account using an email or GitHub login. Once logged in, you'll land on the dashboard. Spend a few minutes browsing the Examples section—these pre-built simulations showcase possibilities like predator-prey dynamics or supply chain optimization. Click into one to see how agents are coded and how results are displayed. This gives you a mental template for your own model.

Step 2: Define Your Problem and Agents

Before writing any code, clarify what you want to simulate. For the warehouse example: agents are workers and items; behaviors include moving, picking up items, and avoiding collisions; environment is the warehouse layout; metrics are throughput (items processed per hour). Write down the key agents and their interactions. This step ensures you stay focused when you start coding.

Step 3: Create a New Simulation

From the dashboard, click New Simulation. Give it a name like “Warehouse Workers”. You can start from a blank canvas or choose a template. For simplicity, select the blank project. HASH opens a code editor with two main files: init.js (initial setup) and step.js (actions taken every time step). You'll also see a 2D/3D visualization pane.

Step 4: Code Agent Behaviors

In init.js, define your agents. For the warehouse, create an array of worker agents. Example:

// init.js
const workers = [];
for (let i = 0; i < 4; i++) {
  workers.push({
    position: {x: i*2, y: 0},
    speed: 1,
    carrying: false
  });
}
states.addAgents('worker', workers);

In step.js, write the logic each agent follows each tick. For workers: if not carrying an item, move toward a random item; if carrying, move toward drop-off point. Avoid collisions by checking other workers' positions. Example snippet:

// step.js
function step(agent, i) {
  if (!agent.carrying) {
    let item = findNearestItem(agent.position);
    if (item) {
      moveToward(agent, item.position);
      if (distance(agent.position, item.position) < 1) {
        agent.carrying = true;
        removeItem(item);
      }
    }
  } else {
    moveToward(agent, {x: 0, y: 0});
    if (distance(agent.position, {x:0,y:0}) < 1) {
      agent.carrying = false;
      incrementScore();
    }
  }
}

Use HASH's built-in APIs like moveToward(), distance(), and states.addAgents(). The platform provides documentation inline.

Step 5: Set Parameters and Run

Add a globals object to store parameters like number of workers or item spawn rate. You can also use sliders in the UI to adjust these without editing code. Click Run to start the simulation. Watch the visualization—are workers colliding? Is throughput high? HASH automatically logs data you can chart, such as items processed over time.

Step 6: Analyze Results and Iterate

After the simulation finishes (or while it runs), inspect the Analysis tab. View graphs, export data, or overlay runs with different parameters. Notice that with 4 workers throughput is high, but with 5 it plateaus or drops due to congestion. Test tweaks: slower speed? Larger warehouse? Change parameters and re-run. Each iteration deepens your understanding.

Tips for Success

Start small. Model just 2-3 agents with simple rules. Add complexity only after your basics work.
Use HASH's example library. Study how others modeled traffic jams or virus spread—their patterns can inspire your code.
Save versions. HASH tracks history. If a change breaks the model, revert easily.
Leverage random input. Run multiple trials with different random seeds to see patterns, not just one outcome.
Visualize everything. Add custom charts using HASH's analysis functions to catch outliers.
Collaborate. HASH supports shared projects. Invite colleagues to build together.

Now head to hash.ai, create your account, and start modeling the world—one agent at a time.

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