The multi-agent version of TORCS for developing control algorithms for fully autonomous driving in the cluttered, multi-agent settings of everyday life.

A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env

Deep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex

Lane keeping assistant using Reinforcement learning

Docker-based, gym-like torcs environment with vision.

PyTorch implementation of Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization (PPO) on TORCS (The Open Racing Car Simulator)

Performance Evaluation of Imitation Learning, DAGGER and HG-DAGGER

autonomous driving in video games

A simple artificially intelligent client run on the torcs server.

A track editor for TORCS

An AI agent based on Supervised Learning for TORCS

Deep learning framework for autonomous driving in TORCS

A server-worker based distributed framework for A3C algorithm implemented for TORCS racing car simulator

Torcs Controller's AI

self driving car using Torcs-1.3.7 simulator with server-patch

AI driver built on Torcs network client

SCR 2013 patch for Torcs 1.3.7

TORCS C++ client with a driver written in Fuzzy Control Language

Self-driving Python Agent using ROS and Deep Learning Algorithm on TORCS. A fork of https://github.com/marsauto/europilot, https://github.com/fmirus/torcs_ros