Results 221 to 230 of about 11,612 (263)

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

The Evolution of Aerosol Jet Printing, A Review: Enhancing Material Versatility and Improvements for Next‐Generation Applications

Advanced Materials Technologies, EarlyView.
Aerosol Jet Printing (AJP) has emerged as a versatile additive manufacturing technique for high‐resolution, conformal, and multi‐material printing. This review highlights advances in printable materials, substrate compatibility, post‐processing, characterization, and process innovations, while critically discussing current challenges and future ...
Chandrachur Chatterjee, Rocco Lupoi, Michael J. Gibbons   +2 more
wiley   +1 more source

Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning

Advanced Optical Materials, EarlyView.
Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam, Chan Y. Park, Min Seok Jang   +2 more
wiley   +1 more source

Machine Learning Enables Inverse Design of Optically Driven Microscopic Metavehicles

Advanced Optical Materials, EarlyView.
Machine‐learning‐based inverse design is used optimize “metavehicles” — flat microparticles based on metagratings that generate a strong lateral optical force from normally incident light. The optimized design exhibits a force efficiency of ∼88% and a measured propulsion speed in water much higher than previously reported, demonstrating that inverse ...
Vasilii Mylnikov, Mahdi Shanei, Mikael Käll   +2 more
wiley   +1 more source

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Imitation and Reinforcement Learning

IEEE Robotics & Automation Magazine, 2010
In this article, we present both novel learning algorithms and experiments using the dynamical system MPs. As such, we describe this MP representation in a way that it is straightforward to reproduce. We review an appropriate imitation learning method, i.e., locally weighted regression, and show how this method can be used both for initializing RL ...
Jens Kober, Jan Peters 0001
openaire   +2 more sources

A cognitive framework for imitation learning

Robotics and Autonomous Systems, 2006
In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of cognitive architecture for learning by imitation in which a rich conceptual ...
CHELLA, Antonio, DINDO, Haris, Infantino, I.   +2 more
openaire   +4 more sources

Imitation: Learning and communication

2000
This paper focuses on our works on imitation in autonomous robots. In a first part, we take into account recent studies in the field of developmental psychology and consider the two functions of imitation (learning and communication) that these studies have stressed.
Andry, Pierre, Moga, Sorin, Gaussier, Philippe, Revel, Arnaud, Nadel, Jacqueline   +4 more
openaire   +2 more sources

Relational Learning by Imitation

2009
Imitative learning can be considered an essential task of humans development. People use instructions and demonstrations provided by other human experts to acquire knowledge. In order to make an agent capable of learning through demonstrations, we propose a relational framework for learning by imitation. Demonstrations and domain specific knowledge are
Grazia Bombini, Nicola Di Mauro, Teresa Maria Altomare Basile, Stefano Ferilli, Floriana Esposito   +4 more
openaire   +2 more sources

Learning birdsong by imitation

Science, 2019
Transforming sensory information into vocal imitation allows young finches to ...
openaire   +2 more sources

Machine learning by imitating human learning

Minds and Machines, 1996
Learning general concepts in imperfect environments is difficult since training instances often include noisy data, inconclusive data, incomplete data, unknown attributes, unknown attribute values and other barriers to effective learning. It is well known that people can learn effectively in imperfect environments, and can manage to process very large ...
Kuo Chin Chang, Tzung-Pei Hong, Shian-Shyong Tseng   +2 more
openaire   +1 more source