Results 71 to 80 of about 298,347 (266)
Advanced Functional Materials, EarlyView.Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
Playing Atari with Deep Reinforcement Learning [PDF]
, 2013 We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning.
Antonoglou, Ioannis +6 more
core +1 more source
Advanced Functional Materials, EarlyView.A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang +9 more
wiley +1 more source
物联网学报, 2023 Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have ...
Cenhuishan LIAO +4 more
doaj +2 more sources
IEEE Access, 2020 The motivation behind our work is to review and analyze the most relevant studies on deep reinforcement learning-based object manipulation. Various studies are examined through a survey of existing literature and investigation of various aspects, namely,
Marwan Qaid Mohammed +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source
Deep Reinforcement Learning Approach for Traffic Light Control and Transit Priority
Future TransportationThis study investigates the use of deep reinforcement learning techniques to improve traffic signal control systems through the integration of deep learning and reinforcement learning approaches.
Saeed Mansouryar +3 more
doaj +1 more source
Structure–Transport–Ion Retention Coupling for Enhanced Nonvolatile Artificial Synapses
Advanced Functional Materials, EarlyView.Nitrogen incorporation into the conjugated backbone of donor–acceptor polymers enables efficient charge transfer and deep ion embedding in organic electrochemical synaptic transistors (OESTs). This molecular‐level design enhances non‐volatile synaptic properties, providing a new strategy for developing high‐performance and reliable neuromorphic devices.
Donghwa Lee +5 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Fibrous benzenetrispeptide (BTP) hydrogels, fabricated via strain‐promoted azide‐alkyne cycloaddition (SPAAC) crosslinking, form robust, bioinert networks. These hydrogels can support 3D cell culture, where cell viability and colony growth depend on the fiber content.
Ceren C. Pihlamagi +5 more
wiley +1 more source
Franklin OpenThis paper evaluates two prominent Deep Reinforcement Learning algorithms, Deep Q-Learning and Twin Delayed Deep Deterministic Policy Gradient, by comparing their learned policies against analytically derived optimal policies in specific game-theoretic ...
Marvin Bongiovi
doaj +1 more source