ml-jku/RA-DT
Retrieval-Augmented Decision Transformer: External Memory for In-context RL
This project offers a sophisticated approach to developing intelligent agents that can learn complex tasks quickly within virtual environments, particularly in scenarios where data is scarce or the environment changes. It takes in observational data and desired outcomes from prior task executions to produce an agent capable of performing tasks more effectively through a novel 'external memory' mechanism. This is for researchers and developers working on advanced reinforcement learning and artificial intelligence, especially those in robotics, game AI, or simulation.
No commits in the last 6 months.
Use this if you are developing AI agents for complex, dynamic virtual environments and need them to learn efficiently from limited prior experience, similar to how humans use past knowledge.
Not ideal if you are looking for an out-of-the-box solution for simpler machine learning tasks, or if your primary focus is on classical supervised learning or basic reinforcement learning approaches.
Stars
24
Forks
1
Language
Python
License
MIT
Category
Last pushed
Oct 27, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/ml-jku/RA-DT"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
denser-org/denser-retriever
An enterprise-grade AI retriever designed to streamline AI integration into your applications,...
rayliuca/T-Ragx
Enhancing Translation with RAG-Powered Large Language Models
neuml/rag
🚀 Retrieval Augmented Generation (RAG) with txtai. Combine search and LLMs to find insights with...
NovaSearch-Team/RAG-Retrieval
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
RulinShao/retrieval-scaling
Official repository for "Scaling Retrieval-Based Langauge Models with a Trillion-Token Datastore".