Results 131 to 140 of about 6,930,474 (290)

Toward Pore‐Engineered 3D‐Printed Materials for Sorption Water Harvesting, Interfacial Evaporation, and Radiative Cooling

Advanced Materials, EarlyView.
Water harvesting, radiative cooling, and interfacial solar evaporation are fundamentally governed by coupled heat, mass, and light transport processes. These processes are mediated by pore architecture, including pore size, connectivity, and hierarchical organization.
Dejan J. Trajkovski, Higgins M. Wilson, Abdallah Y. M. Ali, Jiaxing Xu, Ruzhu Wang, Primož Poredoš   +5 more
wiley   +1 more source

Multi-agent reinforcement learning for planning and scheduling multiple goals

, 2000
Recently, reinforcement learning has been proposed as an effective method for knowledge acquisition of the multiagent systems. However, most researches on multiagent system applying a reinforcement learning algorithm focus on the method to reduce ...
Arai, Sachiyo, Sycara, Katia, Payne, Terry R.   +2 more
core   +1 more source

Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning

Machine Learning: Science and Technology
Reinforcement learning (RL) demonstrated immense success in modeling complex physics-driven systems, providing end-to-end trainable solutions by interacting with a simulated or real environment, maximizing a scalar reward signal. In this work, we propose,
Tobias Kortus, Ralf Keidel, Nicolas R Gauger, Jan Kieseler, Bergen pCT Collaboration   +4 more
doaj   +1 more source

Low-Carbon Urban Freight Optimization: Per-Order Adaptive Mode Mixing with Demonstration-Regularized Constrained Reinforcement Learning

Applied Sciences
Urban last-mile delivery is a rapidly growing source of city-centre emissions, and decarbonizing it without eroding service quality has become imperative for climate goals.
Shukang Zheng, Genhua Ma, Hanpei Yang, Ye Lu, Boxuan Wu   +4 more
doaj   +1 more source

Radiative Thermal Management for Extreme Environments: Mechanisms and Design Strategies

Advanced Materials, EarlyView.
In this review, we discuss the fundamental mechanisms of radiative cooling and solar heating, material and structural design strategies, hybrid approaches integrating additional heat transfer pathways, and durability‐oriented designs addressing environmental stresses.
Hyung Rae Kim, Haeseong Kim, Joo Hwan Ko, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song   +5 more
wiley   +1 more source

A reinforcement learning and sequential sampling model constrained by gaze data.

PLoS Computational Biology
Reinforcement learning models can be combined with sequential sampling models to fit choice-RT data. The combined models, known as RL-SSMs, explain a wide range of choice-RT patterns in repeated decision tasks. The present study shows how constraining an
William M Hayes, Melanie J Touchard
doaj   +1 more source

Compliant Transfer Method for Space Manipulators Based on αPPO-LAG

Mathematics
To address challenges associated with high-dimensional coordination and strict physical constraints in fixed-base space manipulator tool transfer under zero gravity, this paper proposes a preference-conditioned safe reinforcement learning algorithm ...
Lianpeng Li, Di Xin, Mingyang Li, Haibo Zhang, Shuanfeng Xu, Donghao Zhang   +5 more
doaj   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Stochastic Decision Horizons for Constrained Reinforcement Learning

CoRR
We propose stochastic decision horizons (SDH), a theoretically grounded framework for solving constrained RL problems with every-step constraint satisfaction, a desirable property in many real-world applications. In SDH, a constraint violation yields an effective shortening of horizon via a state-action continuation probability.
Nikola Milosevic, Leonard Franz, Daniel Häufle, Georg Martius, Nico Scherf, Pavel Kolev   +5 more
openaire   +3 more sources

Mapping Correlated Environmental Landscapes in the Fluorescence Response of a Pyrenylated Charge‐Transfer Probe via Data‐Driven Nonlinear Regression

Advanced Materials Interfaces, EarlyView.
A pyrenylated donor–acceptor probe exhibits environment‐dependent fluorescence governed by intramolecular charge transfer, restricted molecular motion, and supramolecular organization. Nonlinear regression accurately reconstructs fluorescence responses to viscosity, temperature, concentration, and pH, while correlated parameter maps reveal hidden ...
Harshal V. Barkale, Anakhi Hazarika, Nilanjan Dey   +2 more
wiley   +1 more source