How to Create a Simulation in NetLogo of a Maze-Solving Robot

In this step-by-step guide, we will walk you through the process of creating an engaging maze-solving robot simulation in NetLogo. You will learn the fundamentals of NetLogo, gaining a strong foundation in agent-based modeling and simulation. By immersing yourself in this interactive project, you'll not only have fun but also develop essential programming skills that can be applied to more complex simulations in the future. Follow the instructions below to bring your maze-solving robot to life!

Prerequisites:

Before diving into this project, ensure that you have NetLogo installed on your computer. If you don't have it yet and need NetLogo assignment help, you can download the latest version from the official NetLogo website (ccl.northwestern.edu/netlogo/). Familiarity with basic programming concepts and understanding of how NetLogo works will be beneficial.

Step 1: Setup the Environment

Our first task is to set up the simulation environment for the maze-solving robot. We will create the maze, initialize the robot, and prepare everything for the exciting journey ahead.

```globals [maze] to setup clear-all create-maze create-robot reset-ticks end ```

Explanation:

• We declare a global variable 'maze' to represent the maze structure.
• The setup procedure clears the environment, creates the maze, creates the robot, and resets the simulation's time (ticks).

Step 2: Create the Maze

In this step, we'll define the maze structure using a 2D list in NetLogo. Walls and open spaces will be represented by '1' and '0', respectively. We'll also visually depict the maze by setting patch colors accordingly.

To create-maze

```set maze [ ; A 2D list representing the maze structure [1 1 1 1 1 1 1] [1 0 0 0 0 0 1] [1 1 1 0 1 0 1] [1 0 0 0 0 0 1] [1 1 1 1 1 0 1] [1 0 0 0 0 0 1] [1 1 1 1 1 1 1] ] ask patches with [item 0 0 = 1] [set pcolor black] ; Set walls in the maze to black ask patches with [item 0 0 = 0] [set pcolor white] ; Set open spaces in the maze to white end ```

Explanation:

• The create-maze procedure initializes the maze as a 2D list, where '1' represents walls and '0' represents open spaces.
• We set the color of the patches based on the maze structure, where black represents walls and white represents open spaces.

Step 3: Create the Robot

Now, it's time to introduce our robot turtle agent! We'll create a single robot turtle, give it a distinct shape and color, and position it at the starting point in the maze.

To create-robot

``` crt 1 [ set shape "turtle" set color red setxy 1 1 ; Initial position of the robot in the maze ] end ```

Explanation:

• The create-robot procedure creates a single robot turtle agent, sets its shape to "turtle," color to red, and places it at the starting position (1, 1) in the maze.

Step 4: Move the Robot

This is where the magic happens! We'll define the movement logic for our robot. It will navigate the maze by making decisions based on the current patch's status, either as an open space or a wall.

To move-robot

``` let current-patch patch-here let x xcor let y ycor ifelse item y item x maze = 0 [ face target-patch ; Function to make the robot face the target patch move-to target-patch ; Function to move the robot to the target patch ] [ face random 360 fd 1 ] tick end ```

Explanation:

• The move-robot procedure is responsible for the robot's movement in the maze.
• We define local variables to store the current patch (where the robot is), its x and y coordinates.
• We check if the current patch in the maze is an open space (0). If it is, we make the robot face the target patch (where it wants to move) and move to that patch. Otherwise, if the current patch is a wall (1), we make the robot face a random direction and move forward one step.

Step 5: Solve the Maze

Finally, we'll set the robot in motion to solve the maze. Using a while loop, the robot will continue moving until it reaches the destination, where we've marked it as '2' in the maze structure.

To solve-maze

```while [not at-end] [ move-robot ] end to-report at-end let x xcor let y ycor report item y item x maze = 2 ; Assuming the destination is marked as '2' in the maze end ```

Explanation:

• The solve-maze procedure initiates the process of solving the maze. It keeps moving the robot until it reaches the end.
• The at-end reporter procedure reports true when the robot reaches the end (assuming the destination is marked as '2' in the maze), otherwise false.

Conclusion

By following this guide, you've successfully created a fascinating maze-solving robot simulation in NetLogo. You've gained valuable experience in agent-based modeling and simulation. Feel free to explore further and enhance your simulation with more complex algorithms and features to make the maze-solving experience even more captivating. We encourage you to continue your journey into the world of programming and simulations, and we're here to assist you every step of the way.