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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 ...
We investigated the roles of feedback and attention in training a vernier discrimination task as an example of perceptual learning. Human learning even of simple stimuli, such as verniers, relies on more complex mechanisms than previously expected--ruling ...
Perceptual learning has received enhanced interest during the last years both from theoreticians and experimentalists. Recent experimental results reveal that mechanisms underlying perceptual learning are more complex than previously expected, thereby ruli ...
memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...
In this paper we develop a multi-agent simulation model to explore the issue of learning in interorganizational networks. Though interorganizational network researchers generally agree that when firms form into networks they will gain access to new knowled ...
This paper describes how to combine the JADE agent platform with Repast-provided simulation functions for rapidly developing ail environment for the simulation of complex agent model. The main motivation collies from our requirements concerning the simulat ...
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Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. Existing models have introduced synaptic or neuronal noise to drive this exploration. However, those types o ...
Artificial neural networks are applied to many real-world problems, ranging from pattern classification to robot control. In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron model), and ...
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 ...
