Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...
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 ...
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 ...
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 ...
Asynchronous Deep Double Dueling Q-learning for trading-signal execution in limit order book markets
We employ deep reinforcement learning (RL) to train an agent to successfully translate a high-frequency trading signal into a trading strategy that places individual limit orders. Based on the ABIDES ...
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