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 ...
ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...
Abstract: We propose a new Q-learning-based air-fuel ratio (AFR) controller for a Wankel rotary engine. We first present a mean-value engine model (MVEM) that is modified based on the rotary engine ...
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 ...
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 ...
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 ...
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 ...
"This tutorial shows how to use PyTorch to train a DQN agent on the CartPole-v0 task from the [OpenAI Gym](https://gym.openai.com/).\n", "The agent has to decide ...
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