rl-labs 1.0.0

Comprehensive Reinforcement Learning library containing implementations from Labs 1-7

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

pip install rl-labs