# RL Labs Library

A comprehensive Python library containing reinforcement learning implementations from Labs 1-7. This library provides educational implementations of fundamental RL algorithms using Gymnasium environments.

## Features

- **Lab 1**: Basic agent-environment interaction with FrozenLake
- **Lab 2**: GridWorld MDP implementation with transition probabilities
- **Lab 3**: Markov Reward Processes and Monte Carlo estimation
- **Lab 4**: Policy evaluation and value iteration algorithms
- **Lab 5**: Policy improvement and policy iteration methods
- **Lab 6**: Value iteration with convergence analysis
- **Lab 7**: Temporal Difference learning (MC, TD(0), TD(λ))

## Installation

```bash
pip install rl-labs