This repository contains solutions to a 5x5 Gridworld using various dynamic programming and Monte Carlo methods.

• Iterative Policy Evaluation
• Value Iteration
• Policy Iteration
• Bellman Optimality
• Monte Carlo Exploring Starts
• ε-soft Monte Carlo Control
• Off-Policy Monte Carlo Control with Importance Sampling

The environment includes:

• Special states: Blue, Green, Red, Yellow, and terminal (Black)
• Custom rewards and transitions
• Deterministic and stochastic transitions based on the current state

1. Clone the repository:

   git clone https://github.com/ikenna-nwobodo/grid-world.git
   cd grid-world
   

2. Install dependencies

   pip install numpy random matplotlib