EfficientZero
Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021. (by YeWR)
mctx
Monte Carlo tree search in JAX (by google-deepmind)
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| EfficientZero | mctx | |
|---|---|---|
| 9 | 10 | |
| 825 | 2,203 | |
| - | 2.1% | |
| 0.0 | 0.0 | |
| 4 months ago | 3 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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.
EfficientZero
Posts with mentions or reviews of EfficientZero.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-19.
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[D] GPT-3T: Can we train language models to think further ahead?
Here's an algorithm that is more sample efficient : https://github.com/YeWR/EfficientZero
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MuZero learns to play Teamfight Tactics
Use multiprocessing to have more GPU workers could help. My code based on EfficientZero https://github.com/YeWR/EfficientZero is utilizing CPUs and GPUs to 90%. It uses Ray for multiprocessing and splits Reanalyze into CPU and GPU workers to maximize resource utilization. By the way, it's not converging to optimal policy well: it gets stuck at 50% optimal episode return at with a small amount of training. Have you had this issue before?
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[R] Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning - Epochai Pablo Villalobos et al - Trend of ever-growing ML models might slow down if data efficiency is not drastically improved!
Found relevant code at https://github.com/YeWR/EfficientZero + all code implementations here
- Anyone found any working replication repo for MuZero?
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
Mastering Atari Games with Limited Data – EfficientZero ( Human sample -efficiency! ) Paper: https://arxiv.org/abs/2111.00210 Lesswrong article about the paper: https://www.lesswrong.com/posts/mRwJce3npmzbKfxws/efficientzero-how-it-works Github: https://github.com/YeWR/EfficientZero
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Waymo To Use Chinese Geely Robotaxi Body. This Should Send Shivers Into Western OEMs
Have you seen https://github.com/YeWR/EfficientZero EfficientZero yet? This agent is able to solve problems with unknown rules, where the agent starts only with information about the shape of the inputs and reward feedback. With superhuman ability - it needs less training data than humans do - and SoTA trumping results on the problems it has been tried on. (various atari/Go/chess/etc)
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Why does EfficientZero use SimSiam for temporal consistency instead of MAE / MSE?
Open-source codebase for EfficientZero - am I missing something or the repo is empty?
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[D] Paper Explained - EfficientZero: Mastering Atari Games with Limited Data (Full Video Analysis)
Code: https://github.com/YeWR/EfficientZero
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"EfficientZero: Mastering Atari Games with Limited Data", Ye et al 2021 (beating humans on ALE-100k/2h by adding self-supervised learning to MuZero-Reanalyze)
Code for https://arxiv.org/abs/2111.00210 found: https://github.com/YeWR/EfficientZero
mctx
Posts with mentions or reviews of mctx.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-15.
- About Monte Carlo tree search in Jax
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Programming language dilemma
Maybe you can have your cake and eat it too. :) You could use Python with one of the hardware accelerating languages like Jax. This project for example uses Jax to implement Monte Carlo Tree Search and includes a few games as examples. https://github.com/deepmind/mctx
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Is there any proof that AlphaZero actually exist?
recently tree search part of alpha zero has gone open source https://github.com/deepmind/mctx
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[D] Anyone interested in training an AI for Tigris and Euphrates?
You could try starting with https://github.com/deepmind/mctx. You’ll probably need to expose your game state and actions via IPC of some sort or FFI your rust code to Python.
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DeepMind has open-sourced the heart of AlphaGo and AlphaZero
Interesting approach to private variables https://github.com/deepmind/mctx/blob/577fc77a3cda1b796e277e...
- AlphaZero's Monte Carlo tree search implementation in Jax
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Anyone found any working replication repo for MuZero?
Just have a look at the DM repo: https://github.com/deepmind/mctx
- MuZero Implementation
- Official DeepMind MuZero Implementation
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Finally an official MuZero implementation
deepmind/mctx: Monte Carlo tree search in JAX (github.com)
What are some alternatives?
When comparing EfficientZero and mctx you can also consider the following projects:
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
EfficientZero - Fork of EfficientZero to use newer libraries and to fix a few runtime bugs. Also includes pretrained models!
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
minihack - MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
flash-attention-jax - Implementation of Flash Attention in Jax
KataGo - GTP engine and self-play learning in Go
flash-attention - Fast and memory-efficient exact attention
leela-zero - Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper.
RHO-Loss
alpha-zero-boosted - A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
CodeRL - This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22).
craftingway - A ffxiv crafting tool