Ever since researchers began noticing a slowdown in improvements to large language models using traditional training methods, ...

We examine how techniques like Large Language Models (LLMs), Reinforcement Learning (RL), and Neural Architecture Search (NAS) can address the challenges of modern application performance. Through ...

Article citations More>> Sutton, R.S. and Barto, A. (2020) Reinforcement Learning: An Introduction. Second Edition, The MIT Press. has been cited by the following article: TITLE: Reinforcement ...

Humans estimate different forms of uncertainty during learning, but do so imprecisely, leading to the misattribution of random fluctuations as fundamental shifts.

We apply this model to rats performing a multi-step, reward-learning task and examine the dynamic contribution of various reinforcement learning rules. We successfully capture shifts in strategy ...

Easy explanation of RL concepts This book contains key part of the book "Reinforcement Learning: An Introduction" (pdf) by Richard S. Sutton and Andrew G. Barto. The lecture "Introduction to ...

1 Introduction The purpose of this paper is 2-fold: First, we offer a perspective that links our current understanding of spatial navigation by insect navigation researchers together with that of ...

Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has become one of the most important and useful technology. It is a learning method where a software agent interacts ...