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Implementation of "Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-Agent Urban Driving Environment".

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License: GPL v3

This is a repository for the paper "Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment"

Installattion Setup

  1. Install the system requirements:

    • Ubuntu 18.04+
    • Anaconda (latest version)
    • cmake (sudo apt install cmake)
    • zlib (sudo apt install zlib1g-dev)
    • [optional] ffmpeg (sudo apt install ffmpeg)
  2. Setup CARLA (0.9.4):

Run mkdir ~/software && cd ~/software

Download the 0.9.4 release version from: Here Extract it into ~/software/CARLA_0.9.4

Run echo "export CARLA_SERVER=${HOME}/software/CARLA_0.9.4/CarlaUE4.sh" >> ~/.bashrc

  1. Install the libraries:

Fork/Clone the repository to your workspace:

Create a new conda env named "Benchmarking" and install the required packages: conda env create -f conda_env.yml

Activate the environment: conda activate macad-gym-benchmarking

Run the following commands in sequence for installing rest of the packages to avoid version errors:

pip install -e .

pip install --upgrade pip

pip install -e .

pip install tensorflow==2.1.0

pip install tensorflow-gpu==2.1.0

pip install pip install ray[tune]==0.8.4

pip install pip install ray[rllib]==0.8.4

pip install tf_slim

pip install tensorboardX==2.1

Instructions

Soon to be updated here along with the paper.

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