Table of Contents

Overview †

Here, we introduce how to implement a simple maze task with SkyAI. The maze task has a discrete state and a discrete action, which will be implemented as a module of SkyAI. As an reinforcement learning algorithm, Peng's Q(lambda)-learning is applied to the maze task; of course, we use predefined modules.

The following is the procedure:

  1. Implement a maze task module.
  2. Implement a random action module for testing the task module.
  3. Write an agent script for the random action test.
  4. Write an agent script to apply Q(lambda)-learning.

The sample code works on a console; no extra libraries are required. Let's start!

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Maze Task Module †

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Random Action Module †

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Agent Script for Random Action Test †

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Agent Script for Q(lambda)-learning †

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