Genetic programming and autoconstructive evolution with the push programming language
Push is a programming language designed for the expression of evolving programs within
an evolutionary computation system. This article describes Push and illustrates some of the …
an evolutionary computation system. This article describes Push and illustrates some of the …
[BOOK][B] Biologically inspired algorithms for financial modelling
A Brabazon, M O'Neill - 2006 - books.google.com
Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of
this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In …
this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In …
[BOOK][B] Natural computing algorithms
The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …
decades. One particular strand of this concerns the development of computational …
Defining and simulating open-ended novelty: requirements, guidelines, and challenges
The open-endedness of a system is often defined as a continual production of novelty. Here
we pin down this concept more fully by defining several types of novelty that a system may …
we pin down this concept more fully by defining several types of novelty that a system may …
Evolving the structure of evolution strategies
Various variants of the well known Covariance Matrix Adaptation Evolution Strategy (CMA-
ES) have been proposed recently, which improve the empirical performance of the original …
ES) have been proposed recently, which improve the empirical performance of the original …
[PDF][PDF] Autoconstructive evolution: Push, pushGP, and pushpop
L Spector - Proceedings of the Genetic and Evolutionary …, 2001 - helios.hampshire.edu
This paper is a preliminary report on autoconstructive evolution, a framework for
evolutionary computation in which the machinery of reproduction and diversification (and …
evolutionary computation in which the machinery of reproduction and diversification (and …
Automated design of metaheuristic algorithms: A survey
Metaheuristics have gained great success in academia and practice because their search
logic can be applied to any problem with available solution representation, solution quality …
logic can be applied to any problem with available solution representation, solution quality …
A new crossover operator in genetic programming for object classification
The crossover operator has been considered ldquothe centre of the stormrdquo in genetic
programming (GP). However, many existing GP approaches to object recognition suggest …
programming (GP). However, many existing GP approaches to object recognition suggest …
Evolutionary design of evolutionary algorithms
Abstract Manual design of Evolutionary Algorithms (EAs) capable of performing very well on
a wide range of problems is a difficult task. This is why we have to find other manners to …
a wide range of problems is a difficult task. This is why we have to find other manners to …
Towards practical autoconstructive evolution: Self-evolution of problem-solving genetic programming systems
L Spector - Genetic programming theory and practice VIII, 2011 - Springer
Most genetic programming systems use hard-coded genetic operators that are applied
according to user-specified parameters. Because it is unlikely that the provided operators or …
according to user-specified parameters. Because it is unlikely that the provided operators or …