Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing approaches rely on ...

Python’s been the language of data science since before machine learning was trendy, and now you can use it for building AI ...

Story generation is an importantnatural language processing task that aims to generate coherent stories automatically. While the use of neural networks has proven effective in improving story ...

A research team from Singapore and China has introduced LongWriter-Zero, an AI model that uses reinforcement learning to write texts longer than 10,000 words—without relying on synthetic training data ...

A Reinforcement Learning Environment For Job-Shop Scheduling This folder contains the implementation of the paper "A Reinforcement Learning Environment For Job-Shop Scheduling". It contains the deep ...

This repository contains the implementation of a Reinforcement Learning with Human Feedback (RLHF) system using custom datasets. The project utilizes the trlX library for training a preference model ...

In this network, the learning rules minimize probability mismatches between stimulus-evoked and internally driven activities in all excitatory and inhibitory neurons. This learning paradigm generates ...