Results 51 to 60 of about 137,924 (252)

Multiple Landmark Detection Using Multi-agent Reinforcement Learning [PDF]

, 2019
Accepted in MICCAI 2019, Camera Ready ...
Vlontzos, A, Alansary, A, Kamnitsas, K, Rueckert, D, Kainz, B   +4 more
openaire   +3 more sources

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

Advanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao, Che Liu, Jia Cheng Li, Zhen Hao Fu, Yi Su Huang, Si Qi Huang, Lei Zhang, Jian Wei You, Tie Jun Cui   +8 more
wiley   +1 more source

FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation

Sensors
The increasing volume of traffic has led to severe challenges, including traffic congestion, heightened energy consumption, increased air pollution, and prolonged travel times.
Abdul Wahab Mamond, Majid Kundroo, Seong-eun Yoo, Seonghoon Kim, Taehong Kim   +4 more
doaj   +1 more source

Review of Attention Mechanisms in Reinforcement Learning [PDF]

Jisuanji kexue yu tansuo
In recent years, the combination of reinforcement learning and attention mechanisms has attracted an increasing attention in algorithmic research field.
XIA Qingfeng, XU Ke'er, LI Mingyang, HU Kai, SONG Lipeng, SONG Zhiqiang, SUN Ning
doaj   +1 more source

BenchMARL: Benchmarking Multi-Agent Reinforcement Learning

, 2023
The field of Multi-Agent Reinforcement Learning (MARL) is currently facing a reproducibility crisis. While solutions for standardized reporting have been proposed to address the issue, we still lack a benchmarking tool that enables standardization and reproducibility, while leveraging cutting-edge Reinforcement Learning (RL) implementations.
Bettini, Matteo, Prorok, Amanda, Moens, Vincent   +2 more
openaire   +2 more sources

Solvent‐Free Bonding Mechanisms and Microstructure Engineering in Dry Electrode Technology for Lithium‐Ion Batteries

Advanced Functional Materials, EarlyView.
Dry electrode technology revolutionizes battery manufacturing by eliminating toxic solvents and energy‐intensive drying. This work details two promising techniques: dry spray deposition and polymer fibrillation. How their unique solvent‐free bonding mechanisms create uniform microstructures for thicker, denser electrodes, boosting energy density and ...
Yuhao Liang, Hao Long, Zimo Huang, Ting He, Xueming Chen, Meng Li, Hao Chen, Shanqing Zhang   +7 more
wiley   +1 more source

QiMARL: Quantum-Inspired Multi-Agent Reinforcement Learning Strategy for Efficient Resource Energy Distribution in Nodal Power Stations

AI
The coupling of quantum computing with multi-agent reinforcement learning (MARL) provides an exciting direction to tackle intricate decision-making tasks in high-dimensional spaces.
Sapthak Mohajon Turjya, Anjan Bandyopadhyay, M. Shamim Kaiser, Kanad Ray   +3 more
doaj   +1 more source

Offline Decentralized Multi-Agent Reinforcement Learning

, 2023
In many real-world multi-agent cooperative tasks, due to high cost and risk, agents cannot continuously interact with the environment and collect experiences during learning, but have to learn from offline datasets. However, the transition dynamics in the dataset of each agent can be much different from the ones induced by the learned policies of other
Jiechuan Jiang, Zongqing Lu
openaire   +2 more sources

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Admission-Based Reinforcement-Learning Algorithm in Sequential Social Dilemmas

Applied Sciences, 2023
Recently, the social dilemma problem is no longer limited to unrealistic stateless matrix games but has been extended to temporally and spatially extended Markov games by multi-agent reinforcement learning.
Ting Guo, Yuyu Yuan, Pengqian Zhao
doaj   +1 more source