FourRooms Simulation Project

This Python project simulates an agent navigating through a "FourRooms" grid environment. The project includes multiple scenarios, each representing different challenges and behaviors like deterministic and stochastic actions. The project is designed to help study and demonstrate reinforcement learning techniques.

Project Structure

The project consists of several Python scripts, one for each scenario, and a shared FourRooms.py module that defines the environment.

• Scenario1.py: Handles the simplest case with a single package collection.
• Scenario2.py: Involves multiple package collections without order.
• Scenario3.py: Extends scenario 2 by requiring packages to be collected in a specific order.
• -Stochiastic flag: Introduces stochastic actions where the agent's intended moves might not go as planned.
• FourRooms.py: The environment module used by all scenarios.
• Makefile: Simplifies the setup and running of simulations.

Installation

Prerequisites

• Python 3.6 or higher
• pip (Python package installer)

Create and activate a virtual environment (optional but recommended):

python -m venv venv
source venv/bin/activate  # On Unix or MacOS
venv\Scripts\activate  # On Windows

Install the required packages:

pip install -r requirements.txt

Usage You can run each scenario using the Makefile commands provided. Here are some examples:

Run Scenario 1 (Deterministic):

make run1

Run Scenario 1 (Stochastic):

make run1-stochastic

Running All Scenarios

make all

Cleaning Up To clean up the environment and remove all Python bytecode compiled files:

make clean