dcss-ai-wrapper
nle
| dcss-ai-wrapper | nle | |
|---|---|---|
| 5 | 15 | |
| 38 | 932 | |
| - | - | |
| 3.7 | 3.7 | |
| 3 months ago | 5 days ago | |
| Python | C | |
| MIT License | GNU General Public License v3.0 or later |
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.
dcss-ai-wrapper
- Facebook AI which plays NetHack
-
Publically Exposed/Accessible Crawl Data
Another very interesting project is the dcss-ai-wrapper. Which allows you to interface crawl from a program. You can use it to do reinforcement learning or write rule based bots.
-
DCSS Python Bot (proof of concept)
Is your work related to https://github.com/dtdannen/dcss-ai-wrapper? There is a bit of academic work as well:
- Need help with what to focus my RL thesis on!
-
Is there a consensus about RL frameworks?
DCSS AI Wrapper GitHub (under heavy development at the moment) https://github.com/dtdannen/dcss-ai-wrapper
nle
- What if we set GPT-4 free in Minecraft?
-
Voyager: An LLM-powered learning agent in Minecraft
precisely, I really hope someone does Nethack next and leverages the learning environment that's already customized for it.
-
Analyzer for Nethack idea - problem with getting data from another program
You should look at The Nethack Learning Environment.
-
[D] We're the Meta AI research team behind CICERO, the first AI agent to achieve human-level performance in the game Diplomacy. We’ll be answering your questions on December 8th starting at 10am PT. Ask us anything!
There's quite a few open-source Reinforcement Learning challenges that you can explore with modest amounts of compute in order to build some experience training RL models, for example the Nethack Learning Environment, Atari, Minigrid, etc. For me personally, I had only worked in NLP / dialogue for years but got into RL by implementing Random Network Distillation models for NetHack. It's a fun area that definitely has its own unique challenges vs other domains. -AM
- Facebook AI which plays NetHack
- The NetHack Learning Environment
-
Hacker News top posts: Nov 12, 2022
The NetHack Learning Environment\ (2 comments)
What are some alternatives?
qw - The DCSS-playing bot qw
wa-tunnel - Tunneling Internet traffic over Whatsapp
sequell - ##crawl bot Sequell; depends on https://github.com/crawl/go-sequell
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
LeanQt - LeanQt is a stripped-down Qt version easy to build from source and to integrate with an application.
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
BotHack - BotHack – A Nethack Bot Framework
maze - Maze Applied Reinforcement Learning Framework
Voyager - An Open-Ended Embodied Agent with Large Language Models