Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
How does complexity arise in evolution
Complexity
Coupling Developmental Rules and Evolution to Aid in Planning Network Growth
BT Technology Journal
Through the Labyrinth Evolution Finds a Way: A Silicon Ridge
ICES '96 Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware
A Non-Discrete Approach to the Evolution of Information Filtering Trees
BT Technology Journal
Coupling Developmental Rules and Evolution to Aid in Planning Network Growth
BT Technology Journal
Nature-Inspired Computing Technology and Applications
BT Technology Journal
Biomimetic Representation with Genetic Programming Enzyme
Genetic Programming and Evolvable Machines
Smooth Operator? Understanding and Visualising Mutation Bias
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Redundant representations in evolutionary computation
Evolutionary Computation
An empirical investigation of how and why neutrality affects evolutionary search
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Crossover: the divine afflatus in search
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Expert Systems with Applications: An International Journal
Representations for evolutionary algorithms
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Using differential evolution for symbolic regression and numerical constant creation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
IEEE Transactions on Evolutionary Computation
Population sizing for the redundant trivial voting mapping
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
ICES'07 Proceedings of the 7th international conference on Evolvable systems: from biology to hardware
Representations for evolutionary algorithms
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Incremental or radical? A study of organizational innovation: An artificial world approach
Expert Systems with Applications: An International Journal
Representations for evolutionary algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Digital Ecosystems: Ecosystem-Oriented Architectures
Natural Computing: an international journal
Some steps towards understanding how neutrality affects evolutionary search
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
The importance of neutral mutations in GP
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Designing a morphogenetic system for evolvable hardware
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Representations for evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
| Hi-index | 0.00 |
In natural systems, the organism or phenotype is the result of a complex developmental process that is played out as the genetic information is interpreted. This is in stark contrast to many artificial evolutionary systems in which the phenotype is represented directly in the genetic information and there is no such development. As well as overcoming the obvious practical impossibility of directly specifying an organism in the genotype, the developmental process may yield other desirable properties. One such property is neutrality in which many genotypes develop into the same phenotype. This paper examines the effect of neutral genotype-phenotype mappings on artificial evolutionary systems through examination of an abstract redundant mapping based on a random Boolean network (RBN). It then goes on to examine the genotype-phenotype mapping within a planning tool that evolves instructions for growing telecommunications networks. It is demonstrated how the right kind of redundancy has the potential of significantly aiding the evolvability of a system.