This is an implementation of a multi-rover control problem in a continuous domain using deep reinforcement learning.

The training script is stored in runners as run_contworld.py. To visualize certain results, use the script vis_contworld.py in visualization.

This library requires Python>=3.5 and the packages listed in requirements.txt.

1. rllab is a framework for developing and evaluating reinforcement learning algorithms, developed by Yan Duan, Xi Chen, Rein Houthooft, John Schulman and Pieter Abbeel at Berkeley and OpenAI.

2. rltools is a library that contains helper tools for working with reinforcement learning algorithms, developed by the Stanford Intelligent Systems Laboratory.