Evolutionary computation systems exhibit various emergent phenomena, primary of which is adaptation. In genetic programming, because of the indeterminate nature of the representation, the evolution of both recombination distributions and representations can emerge from the population dynamics. A review of ideas on these phenomena is presented, including theory on the evolution of evolvability through differential proliferation of subexpressions within programs. An analysis is given of a model of genetic programming dynamics that is supportive of the "Soft Brood Selection" conjecture, which was proposed as a means to counteract the emergence of highly conservative code, and instead favor highly evolvable code. 1. Introduction The ...
Abstract. Biological organisms employ various mechanisms to cope with the dynamic environments they ...
It is hypothesised that one of the main reasons evolution has produced such a tremendous diversity o...
Evolutionary algorithms are used to solve a number of optimization problems in the computer science....
Abstract Emergence and its accompanying phenomena are a widespread process in nature. Despite its pr...
: The recently developed genetic programming paradigm provides a way to genetically breed a computer...
We investigate in detail what happens as genetic programming (GP) populations evolve. Since we shall...
Banzhaf explores the concept of emergence and how and where it happens in genetic programming [1]. H...
International audienceI investigate the relationship between adaptation, as defined in evolutionary ...
This paper investigates the relations between biological evolution and computer simulations of evolv...
Evolution’s ability to find innovative phenotypes is an important ingredient in the emergence of com...
This special issue focuses on two emergent properties of artificial evolutionary sys-tems: evolvabil...
Perpetuating evolutionary emergence is the key to artificially evolving increasingly complex systems...
International audienceThe article provides information on the diachronic or dynamical emergence and ...
An evolutionary algorithm was developed to investigate how the biological genetic code may have evol...
Genetic programming is a promising variant of genetic algorithms that evolves dynamic, hierarchical ...
Abstract. Biological organisms employ various mechanisms to cope with the dynamic environments they ...
It is hypothesised that one of the main reasons evolution has produced such a tremendous diversity o...
Evolutionary algorithms are used to solve a number of optimization problems in the computer science....
Abstract Emergence and its accompanying phenomena are a widespread process in nature. Despite its pr...
: The recently developed genetic programming paradigm provides a way to genetically breed a computer...
We investigate in detail what happens as genetic programming (GP) populations evolve. Since we shall...
Banzhaf explores the concept of emergence and how and where it happens in genetic programming [1]. H...
International audienceI investigate the relationship between adaptation, as defined in evolutionary ...
This paper investigates the relations between biological evolution and computer simulations of evolv...
Evolution’s ability to find innovative phenotypes is an important ingredient in the emergence of com...
This special issue focuses on two emergent properties of artificial evolutionary sys-tems: evolvabil...
Perpetuating evolutionary emergence is the key to artificially evolving increasingly complex systems...
International audienceThe article provides information on the diachronic or dynamical emergence and ...
An evolutionary algorithm was developed to investigate how the biological genetic code may have evol...
Genetic programming is a promising variant of genetic algorithms that evolves dynamic, hierarchical ...
Abstract. Biological organisms employ various mechanisms to cope with the dynamic environments they ...
It is hypothesised that one of the main reasons evolution has produced such a tremendous diversity o...
Evolutionary algorithms are used to solve a number of optimization problems in the computer science....