The multi-agent version of TORCS for developing control algorithms for fully autonomous driving in the cluttered, multi-agent settings of everyday life.
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Updated
Feb 28, 2019 - Python
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
Lane keeping assistant using Reinforcement learning
A server-worker based distributed framework for A3C algorithm implemented for TORCS racing car simulator
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
Docker-based, gym-like torcs environment with vision.
An AI agent based on Supervised Learning for TORCS
Performance Evaluation of Imitation Learning, DAGGER and HG-DAGGER
PyTorch implementation of Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization (PPO) on TORCS (The Open Racing Car Simulator)
Deep learning framework for autonomous driving in TORCS
Created for the project related to the "Natural Computation" subject at the University of Salerno.
self driving car using Torcs-1.3.7 simulator with server-patch
TORCS C++ client with a driver written in Fuzzy Control Language
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