Results 41 to 50 of about 544,487 (316)
Efficient Hindsight Experience Replay with Transformed Data Augmentation
Journal of Applied Science and Engineering, 2023 Motion control of robots is a high-dimensional, nonlinear control problem that is often difficult to handle using traditional dynamical path planning means.
Jiazheng Sun, Weiguang Li
doaj +1 more source
Reinforcement Learning: A Survey
Journal of Artificial Intelligence Research, 1996 This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized.
Andrew W. Moore +2 more
openaire +3 more sources
Parallel model-based and model-free reinforcement learning for card sorting performance
Scientific Reports, 2020 The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the assessment of cognitive flexibility. On the WCST, repeating a sorting category following negative feedback is typically treated as indicating reduced cognitive flexibility ...
Alexander Steinke +2 more
doaj +1 more source
Implementing Online Reinforcement Learning with Temporal Neural Networks [PDF]
arXiv, 2022 A Temporal Neural Network (TNN) architecture for implementing efficient online reinforcement learning is proposed and studied via simulation. The proposed T-learning system is composed of a frontend TNN that implements online unsupervised clustering and a backend TNN that implements online reinforcement learning.
arxiv
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems [PDF]
arXiv, 2023 Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significant drawback persists: its poor data efficiency, stemming from its interactive nature.
arxiv
Munchausen Reinforcement Learning
, 2020 International ...
Vieillard, Nino +2 more
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Some Insights into Lifelong Reinforcement Learning Systems [PDF]
arXiv, 2020 A lifelong reinforcement learning system is a learning system that has the ability to learn through trail-and-error interaction with the environment over its lifetime. In this paper, I give some arguments to show that the traditional reinforcement learning paradigm fails to model this type of learning system.
arxiv
Molecular Oncology, EarlyView.This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain +3 more
wiley +1 more source
Curriculum Learning in Reinforcement Learning [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Transfer learning in reinforcement learning is an area of research that seeks to speed up or improve learning of a complex target task, by leveraging knowledge from one or more source tasks. This thesis will extend the concept of transfer learning to curriculum learning, where the goal is to design a sequence of source tasks for an agent to train on ...
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Learning to Utilize Curiosity: A New Approach of Automatic Curriculum Learning for Deep RL
Mathematics, 2022 In recent years, reinforcement learning algorithms based on automatic curriculum learning have been increasingly applied to multi-agent system problems.
Zeyang Lin +4 more
doaj +1 more source