Artificial neurogenesis: An introduction and selective review

9Citations
Citations of this article
30Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this introduction and review—like in the book which follows—we explore the hypothesis that adaptive growth is a means of producing brain-like machines. The emulation of neural development can incorporate desirable characteristics of natural neural systems into engineered designs. The introduction beginswith a review of neural development and neural models. Next, artificial development— the use of a developmentally-inspired stage in engineering design—is introduced. Several strategies for performing this “meta-design” for artificial neural systems are reviewed. This work is divided into three main categories: bio-inspired representations; developmental systems; and epigenetic simulations. Several specific network biases and their benefits to neural network design are identified in these contexts. In particular, several recent studies show a strong synergy, sometimes interchangeability, between developmental and epigenetic processes—a topic that has remained largely under-explored in the literature.

Cite

CITATION STYLE

APA

Kowaliw, T., Bredeche, N., Chevallier, S., & Doursat, R. (2014). Artificial neurogenesis: An introduction and selective review. Studies in Computational Intelligence, 557, 1–60. https://doi.org/10.1007/978-3-642-55337-0_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free