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 ...
Nature

The distinct functions of working memory and intelligence in model-based and model-free reinforcement learning

Human and animal behaviors are influenced by goal-directed planning or automatic habitual choices. Reinforcement learning (RL) models propose two distinct learning strategies: a model-based strategy, ...
Medical Xpress

New look at dopamine signaling suggests neuroscientists' model of reinforcement learning may need to be revised

Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a ...
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 ...
Forbes

The Rise And Rise Of Reinforcement Learning: AI’s Quiet Revolution

Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
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 ...