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''Table of Contents''
#contents
* Overview [#xfb9bf26]
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:
+ Implement a maze task module.
+ Implement a random action module for testing the task module.
+ Write an agent script for the random action test.
+ Write an agent script to apply Q(lambda)-learning.
The sample code works on a console; no extra libraries are required.
Let's start!
* Maze Task Module [#g1d7df27]
* Random Action Module [#x0a9632f]
* Agent Script for Random Action Test [#vdba6662]
* Agent Script for Q(lambda)-learning [#ef68204c]
![[SkyAI]](image/logoxs.png "[SkyAI]")
