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TORCS Dataset Papers With Code

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Descrição
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.
TORCS Dataset Papers With Code
TORCS Dataset Papers With Code
TORCS Dataset Papers With Code
第14回 配信講義 計算科学技術特論A（2021）
TORCS Dataset Papers With Code
Imitation Learning
TORCS Dataset Papers With Code
PDF) Deep-Q Learning for Autonomous Driving System in Simulation Environment
TORCS Dataset Papers With Code
BURST Dataset Papers With Code
TORCS Dataset Papers With Code
PDF) Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles
TORCS Dataset Papers With Code
SUMMIT Dataset Papers With Code
TORCS Dataset Papers With Code
attention_and_driving/self-driving.md at 2.0 · ykotseruba/attention_and_driving · GitHub
TORCS Dataset Papers With Code
Using Keras and Deep Deterministic Policy Gradient to play TORCS
TORCS Dataset Papers With Code
Frontiers Single Shot Corrective CNN for Anatomically Correct 3D Hand Pose Estimation
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