procgen
Procgen Benchmark: Procedurally-Generated Game-Like Gym-Environments (by openai)
ReinforcementLearning.jl
A reinforcement learning package for Julia (by JuliaReinforcementLearning)
| procgen | ReinforcementLearning.jl | |
|---|---|---|
| 3 | 2 | |
| 973 | 566 | |
| 0.5% | 1.6% | |
| 0.0 | 8.7 | |
| 4 months ago | 13 days ago | |
| C++ | Julia | |
| MIT License | 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.
procgen
Posts with mentions or reviews of procgen.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-19.
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Is there a single-task, multi-scene environment using continuous action spaces like gym-super-mario-bros？
Is there a single-task, multi-scene environment using continuous action spaces? Single-task and multi-scene envs are similar to gym-super-mario-bros and CoinRun in procgen .But they are all discrete action spaces. Thank you!!!!!
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My AI projects don't seem to learn, even if I use an official Gym environment. (Python 3.7)
And now "bigfish" from the procgen Gym environments, tested on Stable Baselines 3. (No success)
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Any tutorial on how to create RL C++ environments?
It's not exactly a tutorial, but OpenSpiel has C++ environments ported to Python that are relatively simple and easy to understand. Procgen would be a more complicated reference to check out as well.
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.
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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.
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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
What are some alternatives?
When comparing procgen and ReinforcementLearning.jl you can also consider the following projects:
tiny-differentiable-simulator - Tiny Differentiable Simulator is a header-only C++ and CUDA physics library for reinforcement learning and robotics with zero dependencies.
Agents.jl - Agent-based modeling framework in Julia
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
NetLogo - turtles, patches, and links for kids, teachers, and scientists
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
Numba - NumPy aware dynamic Python compiler using LLVM
RustyNEAT - Rust implementation of NEAT algorithm (HyperNEAT + ES-HyperNEAT + NoveltySearch + CTRNN + L-systems)