Results 111 to 120 of about 6,292,535 (287)

Auxiliary Decision Method for Power Dispatching Based on Flexible Super-Capacitors and Proximal Policy Optimization Algorithm

IEEE Access
To reduce power waste and improve the operational safety of renewable energy grids, this study proposes an auxiliary decision-making method for power dispatching based on flexible super-capacitors and proximal policy optimization algorithms.
Sheng Yang, Jinglong He, Jinming Liu
doaj   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Addressing Limitations to Equitable Access to Healthcare Services for People Living with HIV in Lebanon [PDF]

, 2015
K2P Policy Briefs bring together global research evidence, local evidence and context-specific knowledge to inform deliberations about health policies and programmes.
El Bawab, Lamya, El-Jardali, Fadi
core  

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Proximal Policy Optimization - Ein umfassender Überblick

Diese Arbeit bietet einen umfassenden Überblick über die Proximal Policy Optimization mit dem Ziel, eine klare und vollständige Zusammenfassung ihres historischen Kontexts, ihres aktuellen Stands und ihrer Zukunftsaussichten zu liefern.
Fehringer, Georg
core   +2 more sources

Proximal Policy Optimization for lane following

, 2020
This thesis aimed to apply a state of the art reinforcement learning algorithm named proximal policy optimization on a complicated task with real world applicability in which sensor data is not always reliable. This algorithm was tested on the task of
Geurtjens, R. P.
core   +1 more source

Benchmarking Data‐Driven Control of Octopus‐Inspired Soft Arms in Underwater Environment

Advanced Intelligent Systems, EarlyView.
Underwater soft robots present safe, compliant interaction, yet reproducible control remains scarce. This work presents an open benchmark for octopus‐inspired arms: a smooth, velocity‐diverse data‐collection scheme produces a compact dataset to train a vanilla policy.
Muhammad Sunny Nazeer, Yasmin Tauqeer Ansari, Emanuele Solfiti, Baljinder Singh Bal, Matteo Lo Preti, Barbara Mazzolai, Cecilia Laschi   +6 more
wiley   +1 more source

Multi-agent cooperative confrontation with proximal policy optimization in urban environments

Tongxin xuebao
To address the issue that urban environments often make command systems inefficient and inflexible due to their geospatial complexity and dynamic changes, a multi-agent cooperative confrontation method with proximal policy optimization for urban ...
MI Guangming, ZHANG Hui, ZHANG Jing, ZHUO Li   +3 more
doaj  

A Proximal Policy Optimization method in UAV swarm formation control

Alexandria Engineering Journal
UAV swarms have increasingly replaced human labor in various industries. However, controlling a large group of UAVs can be difficult and, if not done correctly, cause significant financial losses and delays.
Ning Yu, Juan Feng, Hongwei Zhao
doaj   +1 more source

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

Advanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source