Results 121 to 130 of about 6,292,535 (287)

Reinforcement Learning With a Low‐Cost Parallel Linkage Gripper for Static and Dynamic Planar In‐Hand Manipulation

Advanced Intelligent Systems, EarlyView.
Hardware‐learning co‐design combines volar‐plate‐inspired passive‐joint constraints with mechanism‐aware reinforcement learning for a low‐cost parallel‐linkage gripper. The resulting system performs quasi‐static object adjustment and dynamic pinch grasping, demonstrating reliable planar in‐hand manipulation and successful sim‐to‐real transfer. Parallel
Yanzhou Jin, Adam J. Spiers, Yusuke Iwasawa, Yutaka Matsuo, Yaonan Zhu   +4 more
wiley   +1 more source

Multi-Layer Energy Management and Strategy Learning for Microgrids: A Proximal Policy Optimization Approach

Energies
An efficient energy management system (EMS) enhances microgrid performance in terms of stability, safety, and economy. Traditional centralized or decentralized energy management systems are unable to meet the increasing demands for autonomous decision ...
Xiaohan Fang, Peng Hong, Shuping He, Yuhao Zhang, Di Tan   +4 more
doaj   +1 more source

Dual‐View Representation Learning for Deployable Humanoid Whole‐Body Control

Advanced Intelligent Systems, EarlyView.
Humanoid robots must learn control from limited onboard sensing, although simulation provides richer training‐only states. DVP learning pairs these views of each simulated motion and aligns their latent control features inside the policy‐learning loop. This direct, deployment‐aware supervision accelerates learning while the deployed policy relies only ...
Haolin Song, Wengang Zhou, Mingxiao Feng, Houqiang Li   +3 more
wiley   +1 more source

Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning

IET Intelligent Transport Systems
This paper considers the real‐time spatio‐temporal electric vehicle charging navigation problem in a dynamic environment by utilizing a shortest path‐based reinforcement learning approach.
Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu   +1 more
doaj   +1 more source

Addressing Early Identification and Intervention of Children with Disabilities and Developmental Delays in Lebanon [PDF]

, 2018
K2P Policy Briefs bring together global research evidence, local evidence and context-specific knowledge to inform deliberations about health policies and programmes.
Abou Samra, Clara, Souiedan, Sara, Hilal, Nadeen, El-Jardali, Fadi   +3 more
core  

How does the Kids SIPsmartER program impact the sugar‐sweetened beverage intake of students: An investigation beyond total treatment effect in randomized controlled trial

American Journal of Agricultural Economics, EarlyView.
Abstract This study develops and empirically estimates a structural framework to decompose the causal pathways of multilevel behavioral interventions targeting adolescent health behaviors. We apply this framework to the Kids SIPsmartER (KSS) program, a 6‐month, school‐based intervention evaluated through a clustered randomized controlled trial in rural
Naveen Abedin, Wen You, Annie Reid, Kathleen Porter, Brittany Kirkpatrick, Jamie Zoellner   +5 more
wiley   +1 more source

Targeted molecular generation with latent reinforcement learning

Scientific Reports
Computational methods for generating molecules with specific physiochemical properties or biological activity can greatly assist drug discovery efforts. Deep learning generative models constitute a significant step towards that direction.
Ragy Haddad, Eleni E. Litsa, Zhen Liu, Xin Yu, Daniel Burkhardt, Govinda Bhisetti   +5 more
doaj   +1 more source

Risk-Sensitive Distributional Proximal Policy Optimization for Safe Highway Lane-Change Decision-Making

Applied Sciences
Decision-making is a critical module for intelligent vehicles to achieve safe and efficient autonomous driving. However, most existing reinforcement learning-based decision-making methods optimize policies by maximizing the expected return, which may ...
Qing Ye, Rongliang Zhou, Jiakun Huang, Yaxuan Liu, Xiaolin Song   +4 more
doaj   +1 more source

Proximal Deterministic Policy Gradient

, 2020
This paper introduces two simple techniques to improve off-policy Reinforcement Learning (RL) algorithms. First, we formulate off-policy RL as a stochastic proximal point iteration.
Gian Antonio Susto, Marco Maggipinto, Pratik Chaudhari   +2 more
core   +1 more source

Lost in aggregation? On the importance of local food price data for food poverty estimates

American Journal of Agricultural Economics, EarlyView.
Abstract This paper explores within‐country variations in food price dynamics and food poverty estimates by employing local market price data and national consumer price index (CPI) data. Our results show that national CPI data may be useful for approximating national trends but they fail to detect and identify spatial variations in local trends, which
Stephan Dietrich, Valerio Giuffrida, Bruno Martorano, Georg Schmerzeck, Marco Tiberti   +4 more
wiley   +1 more source