Mastering the Dyna Q Learning method by solving Blocking Maze Problem
Welcome to the "Reinforcement Learning using Python" series! In this episode, we tackle the Blocking Maze problem. You'll learn how to implement the Dyna Q Learning algorithm from scratch using just Python to find the optimal policy and navigate the agent to the goal state.
PERFECT FOR:
- Anyone new to Reinforcement Learning (RL)
- Students and engineers looking for a practical, code-first introduction to Value Iteration
- Data Scientists building foundational RL knowledge
TECH STACK:
- Python
- NumPy (for fast array operations)
RESOURCES: Code on Google Colab: https://colab.research.google.com/drive/1tKgC4RhLht2mIYi6AgXV6H7OY_1IK2dk#scrollTo=U_h-gRARiujD&line=3&uniqifier=1
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