drl_grasping
rlcard
Our great sponsors
| drl_grasping | rlcard | |
|---|---|---|
| 4 | 5 | |
| 326 | 2,689 | |
| - | 3.2% | |
| 0.0 | 6.2 | |
| over 1 year ago | 2 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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.
drl_grasping
-
Researchers at The University of Luxembourg Develop a Method to Learn Grasping Objects on the Moon from 3D Octree Observations with Deep Reinforcement Learning
Continue reading| Check out the paper,and github link
- ROS 2 + Ignition + OpenAI Gym Deep RL Example
- ROS 2 + Ignition + OpenAI Gym Tutorial
- Deep Reinforcement Learning for Robotic Grasping from Octrees
rlcard
- [P] Looking for RL or rules-based No-Limit Hold 'Em Work
-
Self play environments
Hi. I’ve decided to do a project to adapt an rl library to support self-play. This is a project so I can teach myself more about building rl systems. I’ve been considering working with the environment system from rlcard https://github.com/datamllab/rlcard/ but wonder if there are other more widely-used self play environment libraries. Thanks.
-
[Project] Making a Poker AI - having trouble with the form of ML to make smart / strong decisions
Can you point me to some active forums for poker bot building? I can only find github repo like https://github.com/datamllab/rlcard, which is mostly reinforcement learning. Whereas SoTA approach like Pluribus is more about game theory.
-
8+ Reinforcement Learning Project Ideas
Build a Poker bot with RLCard
-
What sort of algorithm should I use ? Incomplete information, card game. (Flowchart for reference)
Probably the easiest way for you to get started is to implement your game on an open source RL framework that has working implementations of some basic CFR variations as well as some other self-play algorithms such as NFSP. OpenSpiel and RLCard are two that I am aware of. Depending on the complexity of your game and how strong your agent needs to play, you might be satisfied with the performance you get using by one of these frameworks.
What are some alternatives?
pytorch-blender - :sweat_drops: Seamless, distributed, real-time integration of Blender into PyTorch data pipelines
gym - A toolkit for developing and comparing reinforcement learning algorithms.
robo-gym - An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots.
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
mjai-reviewer - 🔍🀄️ Review mahjong game log with mjai-compatible mahjong AI.
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.
Poker - Fully functional Pokerbot that works on PartyPoker, PokerStars and GGPoker, scraping tables with Open-CV (adaptable via gui) or neural network and making decisions based on a genetic algorithm and montecarlo simulation for poker equity calculation. Binaries can be downloaded with this link:
gym-pybullet-drones - PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
MonsterHunterPortable3rdHDRemake - Personal fork of a texture upscaling project for PSP's Monster Hunter Portable 3rd
lodtree - A simple rust library to help create octrees and quadtrees for chunked level of detail
shengji - An online version of shengji (a.k.a. tractor) and zhaopengyou (a.k.a. Finding Friends)