17-03-2014, 05:21 PM
Abstract
A new hardware developmental model that shows
strong robust transient fault-tolerant abilities and is
motivated by embryonic development and a
honeycomb structure is presented. Cartesian Genetic
Programming (CGP) is used to evolve the cell
structure. A pattern formation problem is realised by
cells with identical evolved structures. The pattern is
shown to recover from various kinds of transient
faults. The fault-tolerance of this structure is not
designed, but evolved under selective pressure in an
environment of chemicals and states. The increased
interactions between cells, brought about by the
honeycomb structure, speeds up the evolutionary
process and simplifies the structure of the evolved
circuits compared to previous embryonic systems.
1. Introduction
Multi-cellular organisms, products of long-term
biological evolution, demonstrate strong principles for
the design of complex systems. Their nascent
behaviours: such as growth, cloning (self-replication)
and healing (self-repair and fault-tolerance), are
attracting increasing interest from electronic
engineers. All of these characteristics are encoded in
the information stored in the genome of the fertilized
cell (zygote). The process of growth from a single
zygote to a mature organism is called development.
The process of development is controlled by
genes, which determine the synthesis of proteins. The
activity of genes sets up the complex interactions
between different proteins, between proteins and
genes within cells, and hence the interactions between
cells. The development of an embryo is determined by
these interactions [1]. Figure 1 shows a representation
of the pattern formation of cells controlled by the
concentrations of a morphogen [1]. Based on the level
of morphogen in each cell, the cells are developed into
different patterns according to threshold values.
Inspired by natural evolution, Evolvable
Hardware (EHW) developed in the last decade as a
new approach using artificial evolution for the design
of electronic systems [2, 3]. It has demonstrated
ability to perform a wide range of tasks from pattern
recognition to adaptive control [4].
A new hardware developmental model that shows
strong robust transient fault-tolerant abilities and is
motivated by embryonic development and a
honeycomb structure is presented. Cartesian Genetic
Programming (CGP) is used to evolve the cell
structure. A pattern formation problem is realised by
cells with identical evolved structures. The pattern is
shown to recover from various kinds of transient
faults. The fault-tolerance of this structure is not
designed, but evolved under selective pressure in an
environment of chemicals and states. The increased
interactions between cells, brought about by the
honeycomb structure, speeds up the evolutionary
process and simplifies the structure of the evolved
circuits compared to previous embryonic systems.
1. Introduction
Multi-cellular organisms, products of long-term
biological evolution, demonstrate strong principles for
the design of complex systems. Their nascent
behaviours: such as growth, cloning (self-replication)
and healing (self-repair and fault-tolerance), are
attracting increasing interest from electronic
engineers. All of these characteristics are encoded in
the information stored in the genome of the fertilized
cell (zygote). The process of growth from a single
zygote to a mature organism is called development.
The process of development is controlled by
genes, which determine the synthesis of proteins. The
activity of genes sets up the complex interactions
between different proteins, between proteins and
genes within cells, and hence the interactions between
cells. The development of an embryo is determined by
these interactions [1]. Figure 1 shows a representation
of the pattern formation of cells controlled by the
concentrations of a morphogen [1]. Based on the level
of morphogen in each cell, the cells are developed into
different patterns according to threshold values.
Inspired by natural evolution, Evolvable
Hardware (EHW) developed in the last decade as a
new approach using artificial evolution for the design
of electronic systems [2, 3]. It has demonstrated
ability to perform a wide range of tasks from pattern
recognition to adaptive control [4].