On the Influence of Informed Agents on Learning and Adaptation Over Networks
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Perceptual learning is the ability to modify perception through practice. As a form of brain plasticity, perceptual learning has been studied for more than thirty years in different fields including psychology, neurophysiology and computational neuroscienc ...
A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...
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We study the dynamics of a network consisting of N diffusively coupled, stable- limit-cycle oscillators on which individual frequencies are parametrized by wk,k=1,...,N. We introduce a learning rule which influences the wk by driving the system t ...
BACKGROUND: An auditory perceptual learning paradigm was used to investigate whether implicit memories are formed during general anesthesia. METHODS: Eighty-seven patients who had an American Society of Anesthesiologists physical status of I-III and were s ...
Perceptual learning is often considered one of the simplest and basic forms of learning in general. Accordingly, it is usually modeled with simple and basic neural networks which show good results in grasping the empirical data. Simple meets simple. Comple ...
In motor learning, training a task B can disrupt improvements of performance of a previously learned task A, indicating that learning needs consolidation. An influential study suggested that this is the case also for visual perceptual learning [1]. Using t ...
Perceptual learning is learning to perceive and is essential for all forms of perception and learning. For a long time it was believed that perceptual learning was a simple process suitable as a model for studying general mechanism of learning. Researchers ...
A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...
In this paper we develop a multiagent simulation model to explore the impact of learning dynamics on the productive implementation of innovations in project networks comprised of designers and contractors. Though researchers generally agree that when firms ...
An initialization mechanism is presented for Kohonen neural network implemented in CMOS technology. Proper selection of initial values of neurons’ weights has a large influence on speed of the learning algorithm and finally on the quantization error of the ...
