Add to ORKGWe present new techniques for synthesizing programs through sequences of mutations. Among these are (1) a method of local scoring assigning a score to each expression in a program, allowing us to more precisely identify buggy code, (2) suppose-expressions which act as an intermediate step to evolving if-conditionals, and (3) cyclic evolution in which we evolve programs through phases of expansion and reduction. To demonstrate their merits, we provide a basic proof-of-concept implementation which we show evolves correct code for several functions manipulating integers and lists, including some that are intractable by means of existing Genetic Programming techniques.Comment: Minor improvement
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
Evolutionary programming can solve black-box function optimisation problems by evolving a population...
The thesis is about linear genetic programming (LGP), a machine learning approach that evolves compu...
Abstract — At the current state of the art, genetic programs do not contain two constructs that comm...
Abstract—The synthesis of exact integer algorithms is a hard task for Genetic Programming (GP), as i...
In this paper we explore a number of ideas for enhancing the techniques of genetic programming in th...
Genetic programming is an approach that utilises the power of evolution to allow computers to evolve...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Genetic Programming (GP) is a technique which uses an evolutionary metaphor to automatically generat...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Evolving programs with explicit loops presents major difficulties, primarily due to the massive incr...
Multiple methods have been developed for Inductive Program Synthesis, i.e., synthesizing programs co...
A representation has been developed that addresses some of the issues with other Genetic Program rep...
[[abstract]]Although genetic programming (GP) is derived from genetic algorithm (GA), there are issu...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
Evolutionary programming can solve black-box function optimisation problems by evolving a population...
The thesis is about linear genetic programming (LGP), a machine learning approach that evolves compu...
Abstract — At the current state of the art, genetic programs do not contain two constructs that comm...
Abstract—The synthesis of exact integer algorithms is a hard task for Genetic Programming (GP), as i...
In this paper we explore a number of ideas for enhancing the techniques of genetic programming in th...
Genetic programming is an approach that utilises the power of evolution to allow computers to evolve...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Genetic Programming (GP) is a technique which uses an evolutionary metaphor to automatically generat...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Evolving programs with explicit loops presents major difficulties, primarily due to the massive incr...
Multiple methods have been developed for Inductive Program Synthesis, i.e., synthesizing programs co...
A representation has been developed that addresses some of the issues with other Genetic Program rep...
[[abstract]]Although genetic programming (GP) is derived from genetic algorithm (GA), there are issu...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
Evolutionary programming can solve black-box function optimisation problems by evolving a population...
The thesis is about linear genetic programming (LGP), a machine learning approach that evolves compu...