ngoxuanphong/ENV
Reinforcement Learning System
This is an open-source Python library for developing and comparing reinforcement learning algorithms in various game environments. It provides a standard way for learning algorithms to interact with environments, taking an agent's strategy as input and evaluating its performance. This is useful for researchers and practitioners in artificial intelligence who want to test and benchmark new AI strategies.
No commits in the last 6 months.
Use this if you are an AI researcher or developer looking for a standardized platform with pre-built game environments to develop and compare different reinforcement learning algorithms.
Not ideal if you are looking for a plug-and-play AI solution for a specific business problem, rather than a development tool for AI algorithms.
Stars
19
Forks
7
Language
Python
License
MIT
Category
Last pushed
Nov 17, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/agents/ngoxuanphong/ENV"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Future-House/aviary
A language agent gym with challenging scientific tasks
strakam/generals-bots
Develop your agent for generals.io!
inspirai/wilderness-scavenger
A platform for intelligent agent learning based on a 3D open-world FPS game developed by Inspir.AI.
jlin816/homegrid
A minimal home grid world environment to evaluate language understanding in interactive agents.
i01000101/Q-Learning-Visualizer
An AI that learns to solve mazes with Q-Learning algorithm ðŸ§