Hybrid preference machines based on inspiration from neuroscience
Cognitive Systems Research
Computing with active dendrites
Neurocomputing
A developmental model of neural computation using cartesian genetic programming
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Coevolution of intelligent agents using cartesian genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Coevolution of Neuro-developmental Programs That Play Checkers
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
In search of intelligent genes: the cartesian genetic programming computational neuron (CGPCN)
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An oscillatory model for multimodal processing of short language instructions
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Evolution of cartesian genetic programs for development of learning neural architecture
Evolutionary Computation
Temporal processing in a spiking model of the visual system
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
A spiking neural network model of multi-modal language processing of robot instructions
Biomimetic Neural Learning for Intelligent Robots
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Presented is a model of an integrate-and-fire neuron with active dendrites and a spike-timing dependent Hebbian learning rule. The learning algorithm effectively trains the neuron when responding to several types of temporal encoding schemes: temporal code with single spikes, spike bursts and phase coding. The neuron model and learning algorithm are tested on a neural network with a self-organizing map of competitive neurons. The goal of the presented work is to develop computationally efficient models rather than approximating the real neurons. The approach described in this paper demonstrates the potential advantages of using the processing functionalities of active dendrites as a novel paradigm of computing with networks of artificial spiking neurons.