Reinforcement Learning - Simulator


The motivation behind this work is to simulate and animate the Reinforcement Learning algorithms to be able to better understand their behavior, which will enable to enhancements to these algorithms. Visualization is a better way of presenting new concepts to others. Our perception about animating these algorithms is to enable the students to get an intuition for the working of these algorithms by the medium of visualization.


Download package This package contains:

rl_sim.jar The jar file to execute this tool
Help This directory have user manual.
Src This directory contains source code.
Reports This directory contains technical reports on this project.
Mazes This directory consist of sample mazes which can be used to play with this tool.

Installation and Execution:

This tool is know to work with Java Runtime Environment(JRE)1.4.2 and above. To install JRE1.4.2 and above visit

Once java is installed and it is in path:

  1. Extract to appropriate directory.
  2. On windows: Start command prompt,
  3. On Linux: Start shell.
  4. Change directory to directory where files are extracted. Then Change directory to go in RL_sim directory.
  5. Execute the command 'java -jar rl_sim.jar'

To create a shortcut on windows:

  1. Right click on desktop, select new, select Shortcut.
  2. Copy command 'java -jar rl_sim.jar' as location of item and click next.
  3. Specify RLSim as name of shortcut and click finish.
  4. Right click on the shortcut and select properties.
  5. In Start in box, specify the absolute path of directory in which RL_sim.jar exists.
  6. Press Apply and Ok. The shortcut is ready for use :)

If you want to recompile and execute from the source code the main class is called


This tool has been developed by Rohit Kelkar and Vivek Mehta, as part of the Extended Course Project for MS in Information Technology with specialization in Robotics Technology, at Robotics Institute, Carnegie Mellon University.

Advisor: Prof. Andrew Moore


For any query regarding this tool, send us an email.
Rohit Kelkar: rohitkelkar28 [AT] yahoo [DOT] com
Vivek Mehta: vivekm [AT] gmail [DOT] com