Results 11 to 20 of about 1,662,190 (297)
Amplification Effect of Ground Motion in Offshore Meandering Sedimentary Valley
Shock and Vibration, 2021 A sedimentary valley has a visible amplification effect on a seismic response, and the current 2D topographies cannot truthfully reflect the twists and turns of a large-scale river valley.
Hailiang Wang +3 more
doaj +1 more source
地质科技通报, 2021 The use of microbially induced carbonate precipitation (MICP) technology to improve the cementation quality of oil and gas well cementing has attracted more and more attention in recent years.
Tianle Liu +5 more
doaj +1 more source
IEEE Access, 2021 A well-designed demand response (DR) program is essential in smart home to optimize energy usage according to user preferences. In this study, we proposed a multiobjective reinforcement learning (MORL) algorithm to design a DR program.
Song-Jen Chen, Wei-Yu Chiu, Wei-Jen Liu
doaj +1 more source
Rainbow: Combining Improvements in Deep Reinforcement Learning [PDF]
AAAI Conference on Artificial Intelligence, 2017 The deep reinforcement learning community has made several independent improvements to the DQN algorithm. However, it is unclear which of these extensions are complementary and can be fruitfully combined. This paper examines six extensions to the DQN
Matteo Hessel +9 more
semanticscholar +1 more source
Experimental Study on Axial Compression of an Insulating Layer through a Composite Shear Wall
Advances in Civil Engineering, 2021 Based on the research of composite walls at home and abroad, a construction method of continuous opening of the insulation layer in the specimen is proposed.
Yuliang Wang, Congcong Wang, Zhixing Cao
doaj +1 more source
Learning an Accurate State Transition Dynamics Model by Fitting Both a Function and its Derivative
IEEE Access, 2022 Learning accurate state transition dynamics model in a sample-efficient way is important to predict the future states from the current states and actions of a system both accurately and efficiently in model-based reinforcement learning for many robotic ...
Youngho Kim, Hoosang Lee, Jeha Ryu
doaj +1 more source
A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
Italian National Conference on Sensors, 2023 Robotic manipulation challenges, such as grasping and object manipulation, have been tackled successfully with the help of deep reinforcement learning systems.
Dong-Ki Han +3 more
semanticscholar +1 more source
Experience-weighted Attraction Learning in Normal Form Games [PDF]
, 1999 In ‘experience-weighted attraction’ (EWA) learning, strategies have attractions that reflect initial predispositions, are updated based on payoff experience, and determine choice probabilities according to some rule (e.g., logit).
Camerer, Colin F., Ho, Teck Hua
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Construction of aggregation operators with noble reinforcement [PDF]
, 2007 This paper examines disjunctive aggregation operators used in various recommender systems. A specific requirement in these systems is the property of noble reinforcement: allowing a collection of high-valued arguments to reinforce each other while ...
Beliakov, Gleb, Calvo, Tomasa
core +1 more source
Effect of Gr Contents on Wear Properties of Al2024/MgO/Al2O3/Gr Hybrid Composites [PDF]
, 2018 In the present study, hybrid metal matrix composites, Al2024/10Al2O3, Al2024/10Al2O3/3MgO, Al2024/10Al2O3/6MgO, Al2024/10Al2O3/3MgO/1.5 Gr, Al2024/10Al2O3/3MgO/3Gr, and reinforcement samples (AA 2024) produced with powder metallurgy process.
Albayrak, S. +3 more
core +1 more source