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TORCS

   Our Latest Projects

Problem description

   Training virtual drivers using AI

   TORCS (The Open Racing Car Simulator) is a driving simulator. It is
   capable of simulating the essential elements of vehicular dynamics such
   as mass, rotational inertia, collision, mechanics of suspensions, links
   and differentials, friction and aerodynamics. Physics simulation is
   simplified and is carried out through Euler integration of differential
   equations at a temporal discretization level of 0.002 seconds. The
   rendering pipeline is lightweight and based on OpenGL that can be
   turned off for faster training. TORCS offers a large variety of tracks
   and cars as free assets. It also provides a number of programmed robot
   cars with different levels of performance that can be used to benchmark
   the performance of human players and software driving agents. TORCS was
   built with the goal of developing Artificial Intelligence for vehicular
   control and has been used extensively by the machine learning community
   ever since its inception.

Problem source (URL)

   https://paperswithcode.com/dataset/torcs

Codebase description

   This project is aimed to develop a self driving car agent in TORCS
   Simulator using Deep Reinforcement's Learning Actor-Critic Algorithm.

Codebase source (URL)

   https://github.com/atul-dhamija/Reinforcement-Learning-on-TORCS
   (experiment itself, no licence specified)
   no-limits

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