https://github.com/carlosagalicia/cleaning-simulation
Simulation of a group of vacuum cleaning agents tasked with cleaning a grid-based room.
https://github.com/carlosagalicia/cleaning-simulation
agent-based-modeling matplotlib mesa python simulation
Last synced: 19 days ago
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Simulation of a group of vacuum cleaning agents tasked with cleaning a grid-based room.
- Host: GitHub
- URL: https://github.com/carlosagalicia/cleaning-simulation
- Owner: carlosagalicia
- License: mit
- Created: 2024-12-28T21:47:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-28T21:56:18.000Z (over 1 year ago)
- Last Synced: 2025-03-03T01:41:40.548Z (over 1 year ago)
- Topics: agent-based-modeling, matplotlib, mesa, python, simulation
- Language: Jupyter Notebook
- Homepage:
- Size: 218 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Cleaning Robots Simulation
This project simulates a group of vacuum cleaning agents tasked with cleaning a grid-based room. The room starts with a defined percentage of dirty cells (dirt agents), and the vacuum cleaners navigate the space, cleaning these cells while avoiding collisions with other agents.
## Overview
- **Functionality:** Simulates a room with dirt agents and vacuum cleaning agents. The vacuums clean the room by detecting and moving to dirty cells.
- **Objective:** Test the cleaning efficiency of vacuum agents by measuring the time and steps needed to clean a predefined percentage of dirty cells.
## Key Features
### 1. Agents and Environment
- **Vacuum Cleaner Agents:** Agents move within the room, clean dirty cells, and measure their efficiency based on cleaned and visited cells.
- **Dirt Agents:** Represent dirty cells that the vacuum agents aim to clean.
- **Room Model:** A grid environment where agents operate, represented using Mesa's `SingleGrid`.
### 2. Simulation Process
- **Random Activation:** All agents act in random order within each step.
- **Data Collection:** Tracks the grid's state and performance metrics such as cleaning efficiency and steps required.
- **Visualization:** Displays animations of the cleaning process and collects statistical data for analysis.
### 3. Customization
- Parameters such as room dimensions, the percentage of dirty cells, and the number of vacuum agents can be adjusted to explore different scenarios.
## Languages and Tools Used
### Python
- **Mesa:** For agent-based modeling and simulation.
- **Matplotlib:** For data visualization and animations.
- **Seaborn:** To enhance the visual appeal of graphs.
- **NumPy and Pandas:** For numerical computations and data handling.
## Installation and Usage
### Requirements
- Python 3.x
- Required libraries:
```bash
pip install mesa==2.3.3 matplotlib seaborn numpy pandas
```
### Instructions
1. Clone the repository:
```bash
git clone https://github.com/carlosagalicia/Cleaning-Simulation.git
```
2. Navigate to the project directory and run the script:
```bash
jupyter notebook cleaning_vacuums_simulation.ipynb
```
3. The program will execute the cleaning simulation and display the results, including animation and performance metrics.
## Visualization and Results
- The grid is visualized using Matplotlib to track the progress of cleaning over time.
- An animation of the cleaning process is created to observe agent behavior step by step.
## Example Output
- **Simulation Metrics:**
- Total steps: `X` (varies based on parameters)
- Efficiency per vacuum cleaner: Displayed in the terminal.
- **Visualization:**
- Animated cleaning process of the grid.
## Customization Options
- Modify these parameters in the script to test different scenarios:
- Room dimensions (`WIDTH`, `HEIGHT`)
- Percentage of initial dirt (`DIRTY_CELLS`)
- Number of vacuum agents (`VACUUMS`)
## Key Learning Areas
### 1. Agent-Based Modeling
- Designing agents with unique behaviors (Vacuum Cleaners and Dirt).
- Implementing interactions between agents and their environment.
### 2. Performance Evaluation
- Measuring and analyzing cleaning efficiency.
- Visualizing the agent-based simulation process.
### 3. Data Collection and Analysis
- Utilizing Mesa's `DataCollector` to record metrics at each simulation step.
## Visual Representation
### Cleaning Progress Animation
- The grid is animated to display the cleaning process, showing vacuums moving and cleaning dirt in real time.
## Visual Representation
Dirty room with robots (initial state)
Cleaned room (final state)
