ReinforcementLearning.jl
A reinforcement learning package for Julia (by JuliaReinforcementLearning)
RustyNEAT
Rust implementation of NEAT algorithm (HyperNEAT + ES-HyperNEAT + NoveltySearch + CTRNN + L-systems) (by aleksander-mendoza)
ReinforcementLearning.jl | RustyNEAT | |
---|---|---|
2 | 2 | |
566 | 0 | |
1.6% | - | |
8.7 | 7.8 | |
16 days ago | over 2 years ago | |
Julia | Rust | |
GNU General Public License v3.0 or later | - |
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.
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.
ReinforcementLearning.jl
Posts with mentions or reviews of ReinforcementLearning.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-23.
-
What framework would you recommend to build a Tetris game AI using reinforcement learning?
I has a look to Julia too. There are nice tools build by JuliaDynamics. I.e. Agents.jl for agent based modeling. It handles collisions. There is also a framework for reinforcement learning. Also for Genetic Algorithms. Then I found a set of libraries related to Geometry. But it seems to be a lot of work to put that together for my use case.
-
Any tutorial on how to create RL C++ environments?
And I know it's another language, but Julia has made significant strides in their RL packages and are pretty easy to integrate with Python
RustyNEAT
Posts with mentions or reviews of RustyNEAT.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-05.
-
Any tutorial on how to create RL C++ environments?
If you want to really speed up your environment several orders of magnitude, you can implement it in cuda/vulkan /opencl. Here is an example of what I did in vulkan https://mobile.twitter.com/MendozaDrosik It allows me to stimulate thousands of agents in parallel. Works wonders especially if you want to use genetic algorithms. If you're interested, I might make python bindings to my minecraft environment. If you write in rust (like I do), then you can add python bindings very easily with PyO3. This is what I did here https://github.com/aleksander-mendoza/RustyNEAT/blob/main/rusty_neat_quick_guide.py (it's GPU accelerated implementation of NEAT algorithm)
- Would I be able to train basic deep RL models on the m1 MacBook Air?
What are some alternatives?
When comparing ReinforcementLearning.jl and RustyNEAT you can also consider the following projects:
Agents.jl - Agent-based modeling framework in Julia
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
NetLogo - turtles, patches, and links for kids, teachers, and scientists
tiny-differentiable-simulator - Tiny Differentiable Simulator is a header-only C++ and CUDA physics library for reinforcement learning and robotics with zero dependencies.
procgen - Procgen Benchmark: Procedurally-Generated Game-Like Gym-Environments
Numba - NumPy aware dynamic Python compiler using LLVM
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
julia - The Julia Programming Language
ReinforcementLearning.jl vs Agents.jl
RustyNEAT vs brax
ReinforcementLearning.jl vs NetLogo
RustyNEAT vs tiny-differentiable-simulator
ReinforcementLearning.jl vs tiny-differentiable-simulator
RustyNEAT vs procgen
ReinforcementLearning.jl vs procgen
RustyNEAT vs Numba
ReinforcementLearning.jl vs brax
RustyNEAT vs open_spiel
ReinforcementLearning.jl vs julia
ReinforcementLearning.jl vs Numba