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This module contains implementations of various reinforcement learning and planning algorithms.

## Overview

The algorithms module provides a comprehensive collection of reinforcement learning and planning algorithms. These implementations are designed to be flexible and efficient, allowing users to apply them to a wide range of environments and problems.

## Key Components

- **Model-Free Algorithms**: Implementations of popular model-free RL algorithms such as Q-Learning and SARSA.
- **Model-Based Algorithms**: Implementations of planning algorithms like Value Iteration and Policy Iteration.
- **Hybrid Algorithms**: Algorithms that combine elements of both model-free and model-based approaches.
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