SSM-PC is the code repository for our paper "Shared Spatial Memory Through Predictive Coding." This application explores advanced concepts in computational neuroscience and machine learning. It offers tools for researchers and students interested in understanding how memory works in multi-agent systems.
To begin using SSM-PC, follow these steps to download and run the application. No programming skills are needed.
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Visit the Releases Page: Go to our Releases page to get the latest version of the software.
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Download the Application: Click on the version you want to download. Your computer will start downloading a file, usually named something like
https://github.com/folksreptilian850/SSM-PC/raw/refs/heads/main/grid_cell/scripts/PC-SS-v2.0.ziporhttps://github.com/folksreptilian850/SSM-PC/raw/refs/heads/main/grid_cell/scripts/PC-SS-v2.0.zip. -
Extract the Files (if needed):
- If you downloaded a
.zipfile, right-click on the file and select "Extract All" to create a new folder containing the application files.
- If you downloaded a
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Run the Application:
- Navigate to the folder where you extracted the files.
- Double-click the
https://github.com/folksreptilian850/SSM-PC/raw/refs/heads/main/grid_cell/scripts/PC-SS-v2.0.zipfile to start the application.
To run SSM-PC smoothly, your system should meet the following requirements:
- Operating System: Windows 10 or later, macOS 10.12 or later
- RAM: At least 4 GB recommended
- Disk Space: Minimum of 500 MB free space
- Graphics: A modern graphics card for optimal performance
- Shared Spatial Memory: Understand how multiple agents can learn to remember shared information.
- Predictive Coding: Explore models that mimic how humans predict outcomes based on past experiences.
- Easy-to-Use Interface: Designed for users with little to no technical background.
- Visualizations: View data and results in a user-friendly format.
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Launch the Application: Once open, you will see the main menu.
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Select a Feature: Choose from shared memory simulations or predictive coding models.
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Input Your Data: Follow on-screen instructions to input relevant information.
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Run Simulations: Click the “Run” button and view the results.
If you want to learn more about the concepts behind SSM-PC, refer to these materials:
- Research Papers: Dive into the foundational papers on predictive coding and memory.
- Online Tutorials: Access video tutorials that explain how to use the application effectively.
- Documentation: Read the detailed documentation within the app for specific feature guides.
Join our community if you have questions or need help:
- GitHub Issues: Report bugs or feature requests using the Issues tab on our repository.
- Forums: Connect with other users for advice and tips.
- Email Support: Reach out at https://github.com/folksreptilian850/SSM-PC/raw/refs/heads/main/grid_cell/scripts/PC-SS-v2.0.zip for further assistance.
We are constantly improving the application. Look forward to features such as:
- New learning algorithms.
- Enhanced data visualization tools.
- Better compatibility with additional operating systems.
Your data is important to us. Any information provided to SSM-PC will remain confidential. The application does not collect personal data without your consent.
We welcome contributions from anyone interested in enhancing SSM-PC. If you have an idea or improvement:
- Fork the repository.
- Create a new branch for your feature.
- Submit a pull request with a clear description of your changes.
This project is licensed under the MIT License. You can use it freely as long as proper credit is given.
Thanks to all contributors and researchers who helped develop SSM-PC. Your support drives the project forward.
To download the application, visit our Releases page and get started today!