Publication

Neural Morphogenesis, Synaptic Plasticity, and Evolution

Dario Floreano, Riadh Abbas
2001
Journal Articles

Abstract

Morphology plays an important role in the computational properties of neural systems, affecting both their functionality and the way in which this functionality is developed during life. In computer-based models of neural networks, artificial evolution is often used as a method to explore the space of suitable morphologies. In this paper we critically review the most common methods used to evolve neural morphologies and argue that a more effective, and possibly biologically plausible, method consists of genetically encoding rules of synaptic plasticity along with rules of neural morphogenesis. Some preliminary experiments with autonomous robots are described in order to show the feasibility and advantages of the approach.

Official source

https://infoscience.epfl.ch/entities/publication/1c01ac39-d5d2-46ee-aba4-e9cd72a1515a

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Dario Floreano, Riadh Abbas
2001
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/1c01ac39-d5d2-46ee-aba4-e9cd72a1515a

About this result

Related concepts (31)

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Evolution

In biology, evolution is the change in heritable characteristics of biological populations over successive generations. Evolution occurs when evolutionary processes such as natural selection (including sexual selection) and genetic drift act on genetic variation, resulting in certain characteristics becoming more or less common within a population over successive generations. The process of evolution has given rise to biodiversity at every level of biological organisation.

Neural network

A neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.

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Neural Morphogenesis, Synaptic Plasticity, and Evolution

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