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leaderboard

CARLA Autonomous Driving leaderboard

macad-agents

Agents code for Multi-Agent Connected Autonomous Driving (MACAD) described in the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

macad-gym

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

mapr2

ml-visuals

Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

ngsim_env

An rllab environment for learning human driver models with imitation learning using NGSIM data

poker_cfr

Understanding Poker rules, Game Theory, and CFR algorithms in order to implement my first CFR solving Rock-Paper-Scissors Game and my first Vanilla CFR solving Kuhn Poker

precog

Reimplementation (currently partial) of PRECOG paper, ICCV '19

pylot

Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.

pytorch-tutorial

Build your neural network easy and fast

pytorch-vae

A Collection of Variational Autoencoders (VAE) in PyTorch.

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

reinforcement-learning

Reinforcement learning baseline agent trained with the Actor-critic (A3C) algorithm.

reward-learning-rl

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

rl-agents

Implementations of Reinforcement Learning algorithms

rl-baselines3-zoo

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

rl-torcs

rllib-integration

Integration of RLLib and CARLA

roll

Implementation for "ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning", CoRL 2020

safe-explorer

Pytorch implementation of "Safe Exploration in Continuous Action Spaces" [Dalal et al.]

saferl

Safe Reinforcement Learning algorithms

safety-gym

Tools for accelerating safe exploration research.

safety-starter-agents

Basic constrained RL agents used in experiments for the "Benchmarking Safe Exploration in Deep Reinforcement Learning" paper.

sat

An autonomous driving agent with a Safety model and the ATtention mechanism in a multi-task framework.

scenario_runner

Traffic scenario definition and execution engine

softlearning

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

softqlearning

Reinforcement Learning with Deep Energy-Based Policies

spinningup

An educational resource to help anyone learn deep reinforcement learning.

stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

stable-baselines3

PyTorch version of Stable Baselines, improved implementations of reinforcement learning algorithms.