Results 81 to 90 of about 1,052,376 (334)

Crop Yield Prediction Using Deep Reinforcement Learning Model for Sustainable Agrarian Applications

IEEE Access, 2020
Predicting crop yield based on the environmental, soil, water and crop parameters has been a potential research topic. Deep-learning-based models are broadly used to extract significant crop features for prediction. Though these methods could resolve the
Dhivya Elavarasan, P. M. Durairaj Vincent   +1 more
doaj   +1 more source

A Deep Reinforcement Learning Chatbot

CoRR, 2017
40 pages, 9 figures, 11 ...
Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Mudumba, Alexandre de Brébisson, Jose Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio   +17 more
openaire   +2 more sources

Why human connection is the true metric of research success

FEBS Open Bio, EarlyView.
Human‐centred mentorship can be shaped by mentor attributes, actions, intrinsic drive and career ambition. Drawing on reflections across Singapore and France, as well as workshop insights from FEBS‐IUBMB ENABLE 2024, this article shows that human‐centred mentorship creates the conditions for sustainable growth, well‐being and retention in research ...
Timothy Lin Yun Tan, Mattias Wei Ren Kon, Xavier Coumoul, Fun Man Fung   +3 more
wiley   +1 more source

From energy provision to protein synthesis: Tunnelling nanotubes as mediators of intercellular metabolic cooperation in cancer

FEBS Open Bio, EarlyView.
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley   +1 more source

A survey of deep reinforcement learning technologies for intelligent air combat

Hangkong gongcheng jinzhan
Major aviation nations and related research institutions are focusing on exploration and research of key technologies for intelligent air combat. Deep reinforcement learning combines the perceptual ability of deep learning with the decision-making ...
LI Ni, LIAN Yunxiao, ZHOU Pan, XIE Feng, TANG Zhili, ZHOU Haoran, CHEN Jun   +6 more
doaj   +1 more source

Deep Reinforcement Factorization Machines: A Deep Reinforcement Learning Model with Random Exploration Strategy and High Deployment Efficiency

Applied Sciences, 2022
In recent years, the recommendation system and robot learning are undoubtedly the two most popular application fields, and the core algorithms supporting these two fields are deep learning based on perception and reinforcement learning based on ...
Huaidong Yu, Jian Yin
doaj   +1 more source

Deep Reinforcement Learning with Decorrelation

CoRR, 2019
Learning an effective representation for high-dimensional data is a challenging problem in reinforcement learning (RL). Deep reinforcement learning (DRL) such as Deep Q networks (DQN) achieves remarkable success in computer games by learning deeply encoded representation from convolution networks.
Borislav Mavrin, Hengshuai Yao, Linglong Kong   +2 more
openaire   +2 more sources

Intelligent Tutoring Systems for Adult Learning in STEM Disciplines

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley   +1 more source

Artificial Intelligence and Mental Well‐Being in Adult Education: Implications for Practice and Professional Responsibility

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley   +1 more source

Bayesian Deep Reinforcement Learning via Deep Kernel Learning

International Journal of Computational Intelligence Systems, 2018
Reinforcement learning (RL) aims to resolve the sequential decision-making under uncertainty problem where an agent needs to interact with an unknown environment with the expectation of optimising the cumulative long-term reward. Many real-world problems
Junyu Xuan, Jie Lu, Zheng Yan, Guangquan Zhang   +3 more
doaj   +1 more source