🦖 INIT. 2D Game Imitation and Reinforcement Learning Environment

🎯 Project Overview

This project is a powerful platform for training AI agents in 2D game environments, using a combination of imitation learning (from human gameplay) and reinforcement learning. One of its standout features is a user-friendly website that allows users to easily design and create custom Gym environments by drawing components such as obstacles, actions, and observations.

By making the process of environment creation simple and visual, this project bridges the gap between game developers, AI researchers, and even non-technical users who want to experiment with AI in various 2D simulations. In addition, this platform has immense potential for real-world applications in fields like robotics and self-driving systems.

🚀 Why This Project?

Traditional AI training requires substantial time and expertise, particularly in defining custom environments and training models. This project aims to democratize AI development for 2D games and real-world tasks by providing:

1. An accessible environment creation tool: Users can draw their own components (e.g., obstacles, characters, sensors) and define essential parameters for AI training.
2. Pretraining with imitation learning: Users can input human gameplay data to help agents quickly learn basic behaviors.
3. Reinforcement learning for optimization: Once pretrained, agents can further improve through exploration and reward-based learning.

🌍 Future Impact

While the project focuses on 2D games, its adaptability extends far beyond that. It lays the groundwork for AI models that can be used in robotics and autonomous systems, where accurate environment design and human-like decision-making are crucial.

In the future, you can use this platform to:

• Train robotic arms to avoid obstacles in dynamic environments.
• Develop self-driving car models that learn from human behavior and refine their driving strategies through reinforcement learning.
• Design real-time decision-making systems for industrial or automated settings.

🎮 Problem Statement

Training AI agents to master 2D games or real-world decision-making tasks involves several challenges:

• Sparse rewards: Agents need to navigate environments where feedback is delayed or infrequent (e.g., survival for long periods or completing specific objectives).
• Complex environments: Games and real-world tasks present unpredictable obstacles and scenarios, requiring agents to adapt and learn quickly.
• Efficient learning: Learning from scratch is computationally expensive. By using human gameplay data (imitation learning), we accelerate the learning process.

🌟 Solution: Accessible Custom Gym Environment

The environment design tool makes it easy to create tailored scenarios with simple visual inputs. Users can draw their custom elements such as:

• Obstacles: Position different types of challenges for the agent (e.g., moving or static).
• Actions: Define the actions the agent can take, whether it's jumping, dodging, moving, or other behaviors.
• Observations: Define the information the agent will see (e.g., distance to obstacles, velocity, and more).

This allows developers, researchers, and even novices to create new environments and simulations without deep technical knowledge.

🎮 User Guide: Create Your Custom Gym Environment

Follow these simple steps to create your custom Gym environment:

1️⃣ Paste the URL of Any 2D Game on the Web!

• 🖱️ Copy the URL of your favorite 2D game and paste it into the input field.
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2️⃣ See the Main Page with the Game and Its Settings

• 🎯 You'll now see the game along with all the key settings and options for customization.
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3️⃣ Draw Attention to Components on the Game Screen

• ✏️ Component for Extracting Symbols: Select areas of interest to extract symbols or information.
• 🏷️ Sprite Component: Tag obstacles, enemies, or key elements on the game screen.
• 🕹️ Movement Component: Mark areas to track the player's position and movements.
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4️⃣ Record Your Gameplay to Create a Custom Gym Environment

• 🎥 Play the game while our system records your gameplay and learns from your interactions.
• ⏺️ Your actions will be logged to create a personalized Gym environment.
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5️⃣ Download Your Custom Gym Environment

• 📥 Once the environment is created, you can download it for further use with imitation and reinforcement learning models.
• 🎉 Congratulations! You've built your own Gym environment for AI training.
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Feel free to reach out if you need any help or have questions! 😊

Disclaimer: This project can only be meaningfully used by one person at a time, due to the limited system resources. Only the