marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
eLife

Q-learning with temporal memory to navigate turbulence

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...
IEEE

Q-Learning Methods for LQR Control of Completely Unknown Discrete-Time Linear Systems

Abstract: This paper focuses on solving the linear quadratic regulator problem for discrete-time linear systems without knowing system matrices. The classical Q-learning methods for linear systems can ...
IEEE

Improved Q-Learning Algorithm Based on Flower Pollination Algorithm and Tabulation Method for Unmanned Aerial Vehicle Path Planning

Abstract: Planning a path is crucial for safe and efficient Unmanned aerial vehicle flights, especially in complex environments. While the Q-learning algorithm in reinforcement learning performs ...
pcguide

What are Q-Learning and Q*? – OpenAI’s secret AI models

On Wednesday, November 22nd, OpenAI CTO Mira Murati sent a letter to employees. The letter detailed a project known internally as Q* (Pronounced Q-Star) or Q-Learning. This project was purported to be ...
GitHub

Create easier tutorial on using (Async)VectorEnvs

Create a more basic tutorial on using (Async)VectorEnvs and why you should learn them. I would say that perhaps taking the already excellent blackjact_agent tutorial and rewriting is using AsyncEnvs ...
Journal of Medical Internet Research

Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad

Objective: We aim to optimize the multistep treatment of patients with head and neck cancer and predict multiple patient survival and toxicity outcomes, and we develop, apply, and evaluate a first ...