Results 91 to 100 of about 16,597 (241)
Imitation trap and catch-up: a benchmark model based on horizontal innovation theory [PDF]
PurposeThe paper introduces the concept of the “imitation trap” to describe a state where economies remain reliant on technological imitation and fail to transition to growth driven by independent innovation.
Feng Wei, Yang Jiao
doaj +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Self-imitation and Environmental Scaffolding for Robot Teaching
Imitative learning and learning by observation are social mechanisms that allow a robot to acquire knowledge from a human or another robot. However to be able to obtain skills in this way the robot faces many complex issues, one of which is that of ...
Chrystopher L. Nehaniv +3 more
doaj
Imitation learning of car driving skills with decision trees and random forests
Machine learning is an appealing and useful approach to creating vehicle control algorithms, both for simulated and real vehicles. One common learning scenario that is often possible to apply is learning by imitation, in which the behavior of an ...
Cichosz Paweł, Pawełczak Łukasz
doaj +1 more source
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won +3 more
wiley +1 more source
Imitation Game: A Model-Based and Imitation Learning Deep Reinforcement Learning Hybrid
Autonomous and learning systems based on Deep Reinforcement Learning have firmly established themselves as a foundation for approaches to creating resilient and efficient Cyber-Physical Energy Systems. However, most current approaches suffer from two distinct problems: Modern model-free algorithms such as Soft Actor Critic need a high number of samples
Veith, Eric MSP +4 more
openaire +2 more sources
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy +3 more
wiley +1 more source
A Fast Anti-Jamming Algorithm Based on Imitation Learning for WSN. [PDF]
Zhou W, Zhou Z, Niu Y, Zhou Q, Ding H.
europepmc +1 more source
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley +1 more source
Designing Asymmetric Memristive Behavior in Proton Mixed Conductors for Neuromorphic Applications
Protonic devices that couple ionic and electronic transport are demonstrated as bioinspired neuromorphic elements. The devices exhibit rubber‐like asymmetric memristive behavior with slow voltage‐driven conductance increase and rapid relaxation, enabling simplified read–write operation.
Nada H. A. Besisa +6 more
wiley +1 more source

