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
Using Keras and Deep Deterministic Policy Gradient to play TORCS
TORCS Dataset  Papers With Code
CARLA Dataset Papers With Code
TORCS Dataset  Papers With Code
Sensors, Free Full-Text
TORCS Dataset  Papers With Code
B Ravi Kiran - CatalyzeX
TORCS Dataset  Papers With Code
Performance after training across all environments for at most 2.5
TORCS Dataset  Papers With Code
Information, Free Full-Text
TORCS Dataset  Papers With Code
Machine Learning Datasets
TORCS Dataset  Papers With Code
Imitation Learning
TORCS Dataset  Papers With Code
Deep_Reinforcement_Learning_for_Autonomous_Driving_A_Survey
TORCS Dataset  Papers With Code
Human-inspired autonomous driving: A survey - ScienceDirect
TORCS Dataset  Papers With Code
attention_and_driving/self-driving.md at 2.0 · ykotseruba/attention_and_driving · GitHub
TORCS Dataset  Papers With Code
Waymo Open Dataset Dataset
TORCS Dataset  Papers With Code
Learning a Driving Simulator – arXiv Vanity
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