About Teachingbox
The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status...
The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners.
Obtaining the teachingbox:
FOR USERS:
If you want to download the latest releases, please visit:
FOR DEVELOPERS:
1) If you use Apache Maven, just add the following dependency to your pom.xml:
org.sf.teachingbox
teachingbox-core
1.2.3
2) If you want to check out the most recent source-code:
git clone teachingbox-core
Documentation:
Features
- Reinforcement Learning
- RL-Environments: nArmedBandit, WindyGridWorld, MountainCar, PoleBalance, PoleSwingUp, CartPole, RL-Glue, DynamicalSystems, Grid-Worlds such as Cliff-Walking (including an Grid-World Editor), Crawling Robot 3D Simulation (PythonGL), etc.
- RL-Learner: RBF, Tabular, TileCoding, Neural-Fitted Q-Iteration
- RL-Policies: Greedy, EpsilonGreedy, Softmax, VDBE / VDBE-Softmax, REINFORCE
- Visualizations: Mountain-Car, PoleBalance, Crawler 3D
Previous Versions
Here you can find the changelog of Teachingbox since it was posted on our website on 2015-04-27 03:00:00.
The latest version is 11.10 and it was updated on 2024-04-22 16:19:06. See below the changes in each version.
Teachingbox version 11.10
Updated At: 2018-04-29
Teachingbox version files
Updated At: 2010-04-09
Changes: Several fixes and updates
Disclaimer
External Download
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