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 ...

Abstract: In this paper, a new data-based Q-learning algorithm is proposed to address the optimal control issue for a class of discrete-time switched affine systems (SASs). The algorithm shifts the ...

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 ...

Q-Learning is another temporal difference (TD) method in reinforcement learning (RL). Q-learning learns the optimal action-value function Q(s,a) without requiring a model of the environment (hence, it ...

To endow the prey with intelligent movement behavior and improve the performance of Golden Jackal Optimization (GJO), a Q-learning Improved Gold Jackal Optimization (QIGJO) algorithm is proposed. This ...

This project implements Value Iteration and Q-Learning algorithms to solve a variety of gridworld mazes and puzzles. It provides pre-defined policies that can be customized by adjusting parameters and ...

Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of ...

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 ...

If OpenAI's new model can solve grade-school math, it could pave the way for more powerful systems. This story is from The Algorithm, our weekly newsletter on AI. To get stories like this in your ...

Add Decrypt as your preferred source to see more of our stories on Google. It was a corporate espionage story even a real human screenwriter couldn’t have dreamed up. OpenAI, which sparked the global ...