This code is a fork of https://github.com/xianhong/DDPG-TORCS I have updated a few lines here and there to run it with the updated Keras and Tensorflow. Please check Environment Setup for more info.
DDPG algorithm codes are based on Github repository : https://github.com/yanpanlau/DDPG-Keras-Torcs DDPG algorithm codes are modified to be compatible with Pyhton/TF/Keras version as mentioned in 'Environment setup'. Minor changes to hyper parameters of the original DDPG codes to reduce computation complexity.
The 'torcs.mp4' file is a video clip capturing a sample racing drive on TORCS after the model having been trained for more than 310K steps.
- OS: Ubuntu 16.04 LTS
- Python 3.5
- Keras 2.2.4
- Tensorflow 1.13.1
- Installation of Visual TORCS for RL learning with color vision 'vtorcs-RL-color' as listed in "Gym-torcs" project (https://github.com/ugo-nama-kun/gym_torcs)
- Installation of software packages of 'mencoder' (for stiching together sequence of PNG files captured by TORCS to a MPEG4 video) and 'xautomation' on Ubuntu.
- Setting TORCS' config/raceengine.xml file to enable video frame capturing (Press 'c' to start/stop video frame capturing)
- Training : run 'python ddpg.py'
- Testing : run 'python ddpg_test.py' (requiring the Actor network model being saved first!)