Aerospace and Mechanical Insider on MSN

Hierarchical reinforcement learning boosts air defense efficiency

Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.
Nature

SINDy-RL for interpretable and efficient model-based reinforcement learning

Deep reinforcement learning (DRL) has shown significant promise for uncovering sophisticated control policies that interact in complex environments, such as stabilizing a tokamak fusion reactor or ...
NextBigFuture

Reinforcement Learning Does NOT Fundamentally Improve AI Models

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...
Geeky Gadgets

Reinforcement Learning for LLMs in 2025

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.
Nature

Development and validation of a reinforcement learning model for ventilation control during emergence from general anesthesia

Ventilation should be assisted without asynchrony or cardiorespiratory instability during anesthesia emergence until sufficient spontaneous ventilation is recovered. In this multicenter cohort study, ...
Semiconductor Engineering

DeepSeek: Improving Language Model Reasoning Capabilities Using Pure Reinforcement Learning

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...
Forbes

The New OpenAI o1 Generative AI Model Makes An Important Right Turn When It Comes To Reinforcement Learning

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...
EurekAlert!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
EurekAlert!

Offline model-based reinforcement learning with causal structured world models

The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...
Aerospace and Mechanical Insider on MSN

AI reinforcement learning tackles fusion plasma instabilities

The DIII-D National Fusion Facility in San Diego, operated by General Atomics, houses the largest and most advanced magnetic ...
International Monetary Fund

AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC model

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...
inc42

What Is Reinforcement Learning? Here’s All You Need to Know

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...