https://github.com/h-iaac/cst-tutorial-babybot
This repository provides the content of the ICDL tutorial, we use a Docker-based environment to integrate infant behavior models using the CST (Cognitive System Toolkit). Tutorial presented at the ICDL (International Conference on Development and Learning).
https://github.com/h-iaac/cst-tutorial-babybot
attention cognitive-architectures cognitive-robotics cognitive-science coppeliasim docker java mimo perception sensorial tutorial
Last synced: 9 months ago
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This repository provides the content of the ICDL tutorial, we use a Docker-based environment to integrate infant behavior models using the CST (Cognitive System Toolkit). Tutorial presented at the ICDL (International Conference on Development and Learning).
- Host: GitHub
- URL: https://github.com/h-iaac/cst-tutorial-babybot
- Owner: H-IAAC
- License: lgpl-2.1
- Created: 2025-07-08T19:49:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-09-16T05:26:54.000Z (10 months ago)
- Last Synced: 2025-09-16T07:23:04.917Z (10 months ago)
- Topics: attention, cognitive-architectures, cognitive-robotics, cognitive-science, coppeliasim, docker, java, mimo, perception, sensorial, tutorial
- Language: Java
- Homepage: https://h-iaac.github.io/cst-tutorial-babybot.github.io
- Size: 34.1 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# cst-tutorial-babybot
This repository provides a complete and reproducible Docker-based environment for training and integrating infant behavior models using the CST (Cognitive System Toolkit). It was developed as part of a tutorial presented at the ICDL (International Conference on Development and Learning).
## 🧠 Project Overview
This repository provides a complete and reproducible Docker-based environment for training and integrating infant behavior models using the CST (Cognitive System Toolkit). It was developed as part of a tutorial presented at the ICDL (International Conference on Development and Learning).
The environment supports:
Multimodal infant modeling with MIMo
Behavioral learning experiments using the BabyBench benchmark
Integration of cognitive models written in Java (CST) with simulation environments
A lightweight graphical interface accessible via web browser (noVNC)
## ✅ Requirements
This project runs entirely inside a Docker container, so the requirements are minimal on your host system.
---
### 🧱 Host System Requirements
These are required **only on your local machine** to build and run the Docker container.
| Requirement | Recommended Version | Purpose |
| ------------------------ | ----------------------------------- | ------------------------------------------------------- |
| **Docker** | 20.10+ | To build and run the development environment |
| **Operating System** | Linux / macOS / Windows (with WSL2) | Linux or WSL2 is recommended for smoother support |
| **Web Browser** | Any (Chrome, Firefox, etc.) | To access the graphical interface via noVNC (port 8080) |
| **Git** | 2.x | To clone BabyBench and MIMo repositories (optional) |
| **CPU with AVX support** | Yes | Recommended for PyTorch performance (MIMo models) |
---
### 📦 Preinstalled Inside the Docker Container
Everything below is already included in the Dockerfile — no need to install manually:
#### 🔧 Languages and Platforms
* **Python** 3.12 (via Miniconda)
* **Java** OpenJDK 17
* **Gradle** 7.6
* **Maven**
* **CST-CLI** (custom `.deb` package pre-installed)
#### 🧠 Python Libraries
Installed via `requirements.txt` from BabyBench and MIMo:
* `torch`, `numpy`, `matplotlib`, `pandas`
* `gymnasium`, `pygame`, `opencv-python`, `pyyaml`
* `websockify` (for VNC proxy)
* `stable-baselines3` *(can be removed as per your Dockerfile)*
#### 🖥️ GUI and Developer Tools
* **Xfce4** (lightweight desktop environment)
* **x11vnc**, **xvfb**, **noVNC** (browser-based GUI)
* **Geany** (code editor with syntax highlighting)
* **Mousepad** (lightweight text editor)
* **xfce4-terminal** (terminal emulator)
---
### 🧪 Additional Skills (Recommended for Usage)
* 🐍 **Basic Python & Conda**: To activate environments and run scripts
* ☕ **Basic Java**: To compile and run `.java` files
* 🧠 **Interest in Developmental AI**: To benefit from BabyBench simulations
* 🐳 **Basic Docker knowledge**: To build, run, and troubleshoot the container