skill-expression-game-analysis vs HandyRL

skill-expression-game-analysis

Finding a method to objectively quantify skill expression in games, using reinforcement learning (by chiamp)

HandyRL

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments. (by DeNA)

reinforcement-learning Pytorch Games policy-gradient Deep Learning Machine Learning distributed-training

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skill-expression-game-analysis		HandyRL
	Project
1	Mentions	1
5	Stars	282
-	Growth	0.0%
0.0	Activity	4.3
over 2 years ago	Latest Commit	about 1 month ago
Python	Language	Python
-	License	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.

skill-expression-game-analysis

Posts with mentions or reviews of skill-expression-game-analysis. We have used some of these posts to build our list of alternatives and similar projects.

Analyzing Skill Expression in Games (with the help of reinforcement learning)
1 project | /r/boardgames | 5 Jan 2022

Full details can be found here: https://github.com/chiamp/skill-expression-game-analysis

HandyRL

Posts with mentions or reviews of HandyRL. We have used some of these posts to build our list of alternatives and similar projects.

Suggestions for board game reinforcement learning methods, frameworks
1 project | /r/reinforcementlearning | 24 Mar 2022

What are some alternatives?

When comparing skill-expression-game-analysis and HandyRL you can also consider the following projects:

adaptdl - Resource-adaptive cluster scheduler for deep learning training.

FedML - FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

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

nes-torch - Minimal PyTorch Library for Natural Evolution Strategies

determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

pytorch-learn-reinforcement-learning - A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.

wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.