Results 41 to 50 of about 8,669,620 (261)

Improvement of Deep Reinforcement Learning Using Curriculum in Game Environment

مجله پژوهش در علوم توانبخشی, 2020
Introduction: Training deep curriculum learning is a kind of smart agent training in which, first the simple acts, and then, the difficult acts are trained to smart agent.
Mohammadreza Mohammadnejad, Morteza Dorrigiv, Farzin Yaghmaee   +2 more
doaj   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Application of deep reinforcement learning in the design and optimization of English continuing education teaching content

Discover Artificial Intelligence
This study discusses the application of deep reinforcement learning in the design and optimization of English continuing education teaching content. Aiming at the one-size-fits-all problem in the traditional education model, it puts forward personalized ...
Jinfeng Ma
doaj   +1 more source

Research Progress in Multi-Domain and Cross-Domain AI Management and Control for Intelligent Electric Vehicles

Energies
Recent breakthroughs in artificial intelligence are accelerating the intelligent transformation of vehicles. Vehicle electronic and electrical architectures are converging toward centralized domain controllers.
Dagang Lu, Yu Chen, Yan Sun, Wenxuan Wei, Shilin Ji, Hongshuo Ruan, Fengyan Yi, Chunchun Jia, Donghai Hu, Kunpeng Tang, Song Huang, Jing Wang   +11 more
doaj   +1 more source

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

Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up

Molecular Oncology, EarlyView.
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani, Laura Mariën, Caro De Weerdt, Sanne Wouters, Laure‐Anne Teuwen, Hans Prenen, Katleen Janssens, Timon Vandamme   +7 more
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

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

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