prabhath-r / dqn_framework_rl-game

Advanced DQN framework for web game automation

DQN Framework for Web-Based Game Automation

Overview

This project develops a customizable Deep Q-Network (DQN) framework for automating web-based games using reinforcement learning. The framework is built with PyTorch and uses Selenium for real-time game data extraction for web games. The primary application is the Chrome Dino game, serving as a baseline model. The framework is tested with multiple open ai gym environemtns to ensure compatibility and extendability.

Installation

1. Clone the repository: git clone https://github.com/prabhath-r/DQN_Framework_RL-Game
2. Install dependencies: pip install -r requirements.txt
3. Run the main script: python main.py --game_env [game_name]

Code Structure

• dqn_agent.py: Implements the DQN agent, capable of decision-making and learning.
• environment.py: Manages the interaction between the DQN agent and the game.
• model.py: Defines the neural network architecture for the DQN agent.
• config.py: Contains hyperparameter settings for the DQN agent.
• train_utils.py: Contains helper functions to dynamically save and load the previous checkpoints
• main.py: The main executable script for training the agent.

Usage

• Training the Agent: Execute main.py with the desired game environment.
• Modifying Hyperparameters: Adjust settings in config.py for custom training scenarios.
• Environment Adaptation: Use environment.py to interface with new or existing game environments.

Key Features

• Customizable DQN Agent: Implements state-of-the-art decision-making and learning capabilities.
• Dynamic Environment Management: Seamlessly integrates with various web-based game environments.
• Flexible Neural Network Architecture: Tailors to specific game dynamics, enhancing learning efficiency.
• Comprehensive Training Suite: Includes tools and scripts for effective training and performance evaluation.

Documentation

• Project Report

References

• Chrome Dino Game Simulation on CodePen
• Double DQN Implementation
• Medium Post on DQN on Chrome Dino
• Custom DQN Architecture Development