Results 31 to 40 of about 503,024 (210)

Generalize Robot Learning From Demonstration to Variant Scenarios With Evolutionary Policy Gradient

Frontiers in Neurorobotics, 2020
There has been substantial growth in research on the robot automation, which aims to make robots capable of directly interacting with the world or human. Robot learning for automation from human demonstration is central to such situation.
Junjie Cao, Weiwei Liu, Yong Liu, Jian Yang   +3 more
doaj   +1 more source

INTEGRATED OPTIMIZATION MODEL OF MANUFACTURING AND TRANSPORTATION PROCESSES

Дискурс, 2018
This paper is devoted to constructing a linear mixed-integer model, finding a method and selecting an algorithm to determine the optimal solution to the production and transportation problem.
R. S. Rogulin, D. E. Pleshanov, P. V. Nechaev   +2 more
doaj   +1 more source

A Generalization of Lindstedt–Poincaré Perturbation Method to Strongly Mixed-Parity Nonlinear Oscillators

IEEE Access, 2020
In this paper, generalization for the Lindstedt-Poincaré perturbation method for nonlinear oscillators to a class of strongly mixed-parity oscillating system is established.
W. P. Sun, C. W. Lim
doaj   +1 more source

Variability in training unlocks generalization in visual perceptual learning through invariant representations

, 2023
Stimulus and location specificity are long considered hallmarks of visual perceptual learning. This renders visual perceptual learning distinct from other forms of learning, where generalization can be more easily attained, and therefore unsuitable for ...
Schwiedrzik, Caspar M., Caspar M. Schwiedrzik, Dizaji, Aslan S., Giorgio L. Manenti, Aslan S. Dizaji, Manenti, Giorgio L.   +5 more
core   +1 more source

Feedback-Based Validation Learning

Computation
This paper presents Feedback-Based Validation Learning (FBVL), a novel approach that transforms the role of validation datasets in deep learning. Unlike conventional methods that utilize validation datasets for performance evaluation post-training, FBVL ...
Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi   +4 more
doaj   +1 more source

Do You See What I See? Deepening Teachers’ Understanding of Linear Equations through Student Interviews

Proceedings of the Annual Meeting of the Georgia Association of Mathematics Teacher Educators, 2014
Many teachers have trouble transitioning their students between natural recursive thinking about the data and algebraic notation for representing linear functions (Zazkis & Liljedahl, 2002).
Tamara Pearson, Kelli Nipper, Catherine Matos   +2 more
doaj   +1 more source

Deferring the learning for better generalization in radial basis neural networks [PDF]

, 2001
Proceeding of: International Conference Artificial Neural Networks — ICANN 2001. Vienna, Austria, August 21–25, 2001The level of generalization of neural networks is heavily dependent on the quality of the training data.
Galván, Inés M., Inés María Galván, Pedro Isasi, José María Valls, Valls, José M., Isasi, Pedro   +5 more
core   +1 more source

A selective learning method to improve the generalization of multilayer feedforward neural networks. [PDF]

, 2001
Multilayer feedforward neural networks with backpropagation algorithm have been used successfully in many applications. However, the level of generalization is heavily dependent on the quality of the training data.
Galván, Inés M., Aler, Ricardo, Valls, José M., Isasi, Pedro   +3 more
core   +1 more source

Visual Discrimination Task in Guppies Using a Simultaneous Matching-to-Sample Procedure

Animals
Cognitive abilities in fish have been widely demonstrated using experimental protocols commonly adopted with mammals and birds. Only a few studies have tested fish in the simultaneous match-to-sample task (sMTS), and mixed evidence regarding their ...
Gabriela Gjinaj, Marco Dadda, Maria Elena Miletto Petrazzini   +2 more
doaj   +1 more source

The advantage of flexible neuronal tunings in neural network models for motor learning

Frontiers in Computational Neuroscience, 2013
Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces.
Ellisha N Marongelli, K A Thoroughman
doaj   +1 more source