fetch-and-slide-HRE-PRE VS autonomous-learning-library

Compare fetch-and-slide-HRE-PRE vs autonomous-learning-library and see what are their differences.

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fetch-and-slide-HRE-PRE autonomous-learning-library
1 2
3 639
- -
0.0 7.6
about 2 years ago about 2 months ago
Python Python
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

fetch-and-slide-HRE-PRE

Posts with mentions or reviews of fetch-and-slide-HRE-PRE. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-18.

autonomous-learning-library

Posts with mentions or reviews of autonomous-learning-library. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-17.

What are some alternatives?

When comparing fetch-and-slide-HRE-PRE and autonomous-learning-library you can also consider the following projects:

dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

turtlebot3_ddpg_collision_avoidance - Mapless Collision Avoidance of Turtlebot3 Mobile Robot Using DDPG and Prioritized Experience Replay

PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

deep_rl_zoo - A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.

learning-to-drive-in-5-minutes - Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

Tetris-deep-Q-learning-pytorch - Deep Q-learning for playing tetris game

Meta-SAC - Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

Fleet-AI - Using Reinforcement Learning to play Battleship

skrl - Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Isaac Orbit and Omniverse Isaac Gym