RLPark Documentation

Documentation is usually written on requests. If the code is unclear and you would like a specific point to be documented in RLPark, please send an email to the group with the appropriate information.

RLPark repository:

Github repository: https://github.com/rlpark/rlpark

Code snippets on reinforcement learning:

• Sarsa on Mountain Car
• QLearning in a Maze
• Actor-critic on the Pendulum with Continuous Action
• Off-PAC learning off-policy in a 2D continuous world

Other documentation:

• Using Scheduling for Running Jobs in Parallel
• Using the video: an example of motion detection
• Testing the correctness of an algorithm
• Working with RLPark source code

iRobot repository:

    
Github repository: https://github.com/rlpark/irobots

Code snippets:

• iRobot Create Introduction Session
• Using an iRobot Create
• iRobot Create being surprised
• Using an iRobot Create in Jython

Dynamixel repository:

    
Github repository: https://github.com/rlpark/dynamixel

Code snippets:

• Using a set of motors

Critterbot repository:

    
Github repository: https://github.com/rlpark/critterbot

Code snippets:

• Using the Critterbot
• The horde architecture in Jython

Links

• Documentation generated from the code source
• iRobot Create Introduction Session
• RLPark on github: https://github.com/rlpark/rlpark

Learning more about reinforcement learning

The following two books are available online:

• Reinforcement Learning: An Introduction (Sutton & Barto, 1998)
• Algorithms for Reinforcement Learning (Szepesvári, 2010)